RespCode Documentation

Multi-model AI code generation with real hardware verification.

RespCode orchestrates multiple AI models (Claude, GPT, DeepSeek, Gemini, and more) to generate, compile, and verify code across multiple architectures β€” x86, ARM64, and ARM32 baremetal β€” using Daytona sandboxes and Firecracker microVMs.

πŸ€–

Hardware Agent

CLI tool that generates code, compiles in the cloud, and deploys to real hardware β€” MCUs, SBCs, or your local machine.

🌐

Web Platform

Browser-based multi-model code generation with real-time streaming and sandbox execution. Free & unlimited.

πŸ’»

VS Code Extension

Generate and compare multi-model code directly from your editor. Coming Soon

πŸ”Œ

MCP Server

Connect RespCode to Claude Desktop, Cursor, and other MCP-compatible clients. Coming Soon

Quick Start

Hardware Agent (recommended for embedded development)

# Install the agent $ curl -fsSL https://respcode.com/agent/install.sh | sh # Run it β€” the agent will ask for your API key on first run $ respcode-agent # Get your API key at https://respcode.com/settings/api-keys

Web Platform

Visit respcode.com, sign up, and start generating code immediately in your browser. The web platform is free with unlimited generations.


Hardware Agent

Generate code in the cloud. Deploy and verify on real hardware.

The RespCode Hardware Agent is a CLI tool that connects your physical development boards to the RespCode cloud. It generates code using AI models, compiles in sandboxes, then deploys the binary to your actual hardware β€” STM32, NXP, Nordic, Pico, TI, Microchip and other ARM development boards via pyOCD/UF2, Linux Single Board computer via SSH, test Cloud instances or your local machine directly.

πŸ’‘ How it works

You type a prompt β†’ cloud generates + compiles β†’ agent downloads binary β†’ flashes/deploys to your board β†’ reads UART/stdout output β†’ shows pass/fail. All from one command.

Installation

One-line install (Linux & macOS)

$ curl -fsSL https://respcode.com/agent/install.sh | sh

This will:

Supported platforms

OSArchitectureBinary
Linuxx86_64respcode-agent-linux-amd64
LinuxARM64respcode-agent-linux-arm64
macOSApple Siliconrespcode-agent-darwin-arm64
macOSIntelrespcode-agent-darwin-amd64

Manual install

# Download directly $ curl -fsSL https://respcode.com/agent/releases/latest/respcode-agent-linux-amd64 -o respcode-agent $ chmod +x respcode-agent $ sudo mv respcode-agent /usr/local/bin/

Verify installation

$ respcode-agent --help $ respcode-agent --version respcode-agent v0.8.0

First Run & API Key

When you first run the agent, it will show the board picker and prompt for your API key:

$ respcode-agent β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ Hardware Agent v0.8.0 Plan: β€” β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ Configured targets: (1) Local Machine [sbc Β· x86 Β· localhost] ❯ 1 [ok ] Board: Local Machine [x86 Β· localhost] Cloud: ● disconnected [ok ] Localhost ready [x86] ⚠ No API key configured. Get your key at: https://respcode.com/settings/api-keys Type /key to set your API key, or 'help' for commands. ❯ /key Paste your API key: rc_live_β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ [ok ] Connected β€” 500 credits remaining [ok ] API key saved to ~/.config/respcode/boards.yaml
βœ… No API key required to explore

The agent runs without a key β€” you can browse boards, check hardware, run /boards for examples. You only need the key when generating code.

Get your API key at: respcode.com/settings/api-keys

Configuration

The agent reads its configuration from boards.yaml. It searches these locations in order:

  1. Explicit --config path/to/boards.yaml flag
  2. Current working directory: ./boards.yaml
  3. XDG config: ~/.config/respcode/boards.yaml
  4. Same directory as the binary

The install script creates the default config at ~/.config/respcode/boards.yaml:

~/.config/respcode/boards.yaml
respcode:
  api_url: "https://respcode.com/api"
  api_key: "${RESPCODE_API_KEY}"     # set via /key command or env var

agent:
  max_retries: 3                    # retry attempts on failure
  uart_timeout_seconds: 10
  flash_timeout_seconds: 30
  output_dir: "respcode-output"     # where artifacts are saved

boards:
  - id: "local"
    type: "sbc"
    board_name: "Local Machine"
    architecture: "x86"             # auto-detected during install
    connection: "localhost"
    verify:
      timeout: 30

Adding Boards

Add boards by editing boards.yaml or using the /boards commands inside the agent. The agent supports three board types and auto-detects USB boards on every startup.

Baremetal MCU (Flash + UART)

For microcontrollers like STM32, NXP and other ARM baremetal MCU using pyOCD. The agent first compiles the binary in cloud, verifies there are no errors and later uses pyOCD to flash firmware and reads UART output for verification.

boards.yaml β€” Baremetal example
  - id: "nucleo-f767zi"
    type: "bare-metal"
    mcu: "STM32F767ZI"
    board_name: "NUCLEO-F767ZI"
    architecture: "arm32-baremetal"
    flash:
      tool: "pyocd"
      target: "stm32f767zi"          # pyocd target name
      address: "0x08000000"          # flash start address
      interface: "stlink"           # stlink, cmsis-dap, jlink
      speed_khz: 4000
    uart:
      port: "/dev/ttyACM0"           # ls /dev/ttyACM* to find yours
      baud: 115200
    board_info:
      led_pin: "PB0"
      led_active: "high"
      uart_pins: "PD8 (TX) / PD9 (RX) on USART3"
      clock: "216MHz HSE"
      ram: "512KB @ 0x20000000"
      flash_size: "2MB"
πŸ’‘ Finding your serial port

Linux: Run ls /dev/ttyACM* or ls /dev/ttyUSB*. macOS: Run ls /dev/cu.usbmodem*. Or use the ports command inside the agent.

Required fields for baremetal:

FieldDescriptionExample
typeMust be "bare-metal"bare-metal
mcuMCU part number (used in prompt enrichment)STM32F767ZI
architecturearm32-baremetalarm32-baremetal
flash.toolpyocd, uf2, or openocdpyocd
flash.targetpyOCD target IDstm32f767zi
uart.portSerial port path/dev/ttyACM0
board_info.led_pinLED pin name (for prompts)PB0
board_info.uart_pinsUART pin description (for prompts)PD8/PD9 on USART3

SBC via SSH

For single-board computers like Raspberry Pi, Jetson, BeagleBone, or any Linux machine reachable via SSH. Code is first compiled and executed in the cloud sandbox, then SCP'd to the target and executed via SSH. Use /boards ssh in the agent for an interactive setup wizard with presets for common boards.

boards.yaml β€” SSH SBC example
  - id: "rpi4"
    type: "sbc"
    board_name: "Raspberry Pi 4"
    architecture: "arm64"          # or "arm32" for 32-bit OS
    ssh:
      host: "192.168.1.50"
      user: "pi"
      key: "~/.ssh/id_rsa"          # path to private key
      port: 22
    verify:
      timeout: 10                  # execution timeout in seconds
      expect: ""                   # optional: expected output pattern

Localhost

Run code directly on your local machine without SSH. Code is compiled in the cloud, downloaded, and executed locally. Great for quick testing.

boards.yaml β€” Localhost example
  - id: "local"
    type: "sbc"
    board_name: "Local Machine"
    architecture: "x86"             # or "arm64" on Apple Silicon / ARM Linux
    connection: "localhost"
    verify:
      timeout: 30
⚠️ Architecture matters

Set architecture to match your machine. Use "x86" for Intel/AMD, "arm64" for Apple Silicon or ARM Linux. The install script auto-detects this.

Raspberry Pi Pico (UF2)

For RP2040-based boards that flash via UF2 mass storage. Hold BOOTSEL while plugging in β€” the board mounts as a USB drive, and the agent copies the UF2 binary directly.

boards.yaml β€” Pico example
  - id: "rpi-pico"
    type: "bare-metal"
    mcu: "RP2040"
    board_name: "Raspberry Pi Pico"
    architecture: "arm32"
    flash:
      tool: "uf2"
      mount: "/Volumes/RPI-RP2"      # macOS β€” use /mnt/rpi-rp2 on Linux
    uart:
      port: "/dev/cu.usbmodem1101"  # CDC USB serial
      baud: 115200
    board_info:
      led_pin: "GPIO25"
      led_active: "high"
      uart_pins: "UART0 on GP0 (TX) / GP1 (RX)"
      clock: "125MHz from XOSC 12MHz + PLL"
      ram: "264KB @ 0x20000000"
      flash_size: "2MB @ 0x10000000"

Nordic nRF (pyOCD)

For Nordic nRF52/nRF53 development kits with on-board J-Link or CMSIS-DAP debug probe.

boards.yaml β€” Nordic nRF52840-DK example
  - id: "nrf52840"
    type: "bare-metal"
    mcu: "NRF52840"
    board_name: "nRF52840-DK"
    architecture: "arm32-baremetal"
    flash:
      tool: "pyocd"
      target: "nrf52840"
      address: "0x00000000"
      interface: "cmsis-dap"
    uart:
      port: "/dev/ttyACM0"
      baud: 115200

Auto-Detection

The agent automatically detects new USB boards every time it starts. If you plug in a board after installation, just restart the agent β€” it will find the board, add it to boards.yaml, and install the required pyOCD target pack.

$ respcode-agent [ok ] New board detected: STM32 (ST-Link V2) β†’ added to config [ok ] New board detected: Raspberry Pi Pico β†’ added to config

Supported debug probes (auto-detected on Linux & macOS)

Board FamilyUSB Vendor IDFlash ToolExamples
STM320x0483pyOCD (ST-Link)Nucleo-F767ZI, Discovery, Nucleo-F411RE
NXP LPC0x1fc9pyOCD (CMSIS-DAP)LPC55S69-EVK, LPCXpresso
CMSIS-DAP0x0d28pyOCDmbed-enabled boards
Raspberry Pi Pico0x2e8aUF2 copyPico, Pico W, Pico 2
Nordic nRF0x1915pyOCDnRF52840-DK, nRF5340-DK
TI0x0451OpenOCDMSP432, CC3220, TM4C
SEGGER J-Link0x1366J-LinkAny J-Link connected target
Microchip / Atmel0x03ebOpenOCDSAM, PIC32
πŸ’‘ macOS serial ports

On macOS, serial ports appear as /dev/cu.usbmodemXXXX instead of /dev/ttyACM0 on Linux. The agent detects this automatically. Use the ports command inside the agent to list available ports.

Adding SBC targets interactively

For SSH-based boards (Raspberry Pi, Jetson, BeagleBone, cloud instances), use the built-in wizard:

❯ /boards ssh Common SBC targets: (1) Raspberry Pi 4/5 arm64 user: pi (2) Raspberry Pi 3/Zero 2W arm64 user: pi (3) Raspberry Pi Zero/Zero W arm32 user: pi (4) NVIDIA Jetson Nano arm64 user: jetson (5) NVIDIA Jetson Orin arm64 user: jetson (6) BeagleBone Black arm32 user: debian (7) BeagleBone AI-64 arm64 user: debian (8) Orange Pi 5 arm64 user: orangepi (9) Rock Pi 4 / Radxa arm64 user: rock (10) ARM64 cloud instance arm64 user: ubuntu (11) x86 cloud instance x86 user: ubuntu (12) Generic Linux (custom) β€” β€” Pick [1-12]: 1 SSH host (IP or hostname): 192.168.1.50 SSH user [pi]: SSH key path [~/.ssh/id_rsa]: SSH port [22]: Testing SSH connection to pi@192.168.1.50... [info ] Remote reports aarch64 β€” using arm64 [ok ] SSH connection verified βœ“ [ok ] Added Raspberry Pi 4/5 (pi@192.168.1.50) [arm64]

The wizard prefills board name, architecture, and SSH username from the preset. You only need to enter the IP address and SSH key path. It also tests the connection and auto-detects the remote architecture via uname -m.

Modes & Tiers

After connecting, select your mode and tier at the prompt. Use shortcodes like C1, S2, C4:

Mode: [C]ompete [S]ingle model Tier: [1] Flagship (29cr) [2] Mid (17cr) [3] Budget (6cr) [4] Open Source (8cr) Examples: C1 = Compete+Flagship, S2 = Single+Mid, C4 = Compete+Open Source Press Enter for defaults (Compete + Flagship) ❯ C1 [ok ] Mode: compete · Flagship (29cr)
ShortcodeModeTierCreditsModels
C1CompeteFlagship29Claude Opus, GPT-5, Gemini 3 Pro, DeepSeek Coder
C2CompeteMid17Claude Sonnet, GPT-4o, Gemini Flash, DeepSeek V3
C3CompeteBudget6Claude Haiku, GPT-4o Mini, Gemini Flash
C4CompeteOpen Source8Llama 4, Qwen 3, DeepSeek, Mistral
S1SingleFlagshipvariesPick one model from flagship tier

Change mode anytime with /mode.

Commands Reference

CommandDescription
<any prompt>Generate code, compile, and deploy
rerunRe-run the last prompt (new generation)
Hardware
flash <path>Flash a local .bin file and verify via UART
reflashRe-download and flash the last successful generation
uartListen on UART (no flash)
probeCheck if target is connected
portsList available serial ports
Cloud
download <gen_id>Download all artifacts for a generation
statusShow board + cloud status
Session
/keySet or change your API key
/modeChange mode (compete/single) and tier
/boardSwitch to a different board
/boardsList configured boards and management commands
/boards sshInteractive wizard to add SBC targets (Pi, Jetson, BeagleBone...)
/boards addAdd a board interactively
/boards probeAuto-detect MCU via pyOCD and update config
/boards remove NRemove board #N from config
resultsShow compile results from last generation
historyShow last prompt and generation info
helpShow all commands
quitExit the agent

Workflow

Here's what happens when you type a prompt:

❯ UART and LED blink program on STM32 F767 Generate firmware for: blink LED on STM32 F767 [Compete Flagship (29cr)] Proceed? (y/n) y ━━━ GENERATE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [cloud ] Compete: flagship tier generating for NUCLEO-F767ZI... [cloud ] Models: claude-opus-4-6, gpt-5-2, gemini-3-pro, deepseek-coder [cloud ] claude-opus-4-6 βœ“ done (12 chunks) [cloud ] gpt-5-2 βœ“ done (15 chunks) ... ━━━ COMPILE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [gcc ] claude-opus-4-6 βœ… compiled (0.8s) [gen:3110] [gcc ] gpt-5-2 βœ… compiled (0.6s) [gen:3111] ... ━━━ FLASH + VERIFY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [pyocd ] Flashing 14.2KB to 0x08000000... [pyocd ] β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ 100% (0.4s) [uart ] LED blink initialized on PB0 [uart ] Toggling LED every 500ms... [ok ] βœ… claude-opus-4-6 verified on NUCLEO-F767ZI

The 3-attempt retry system:

  1. Attempt 1: Normal compete/single generation
  2. Attempt 2: If all models fail β€” Claude Sonnet reviews the errors and generates a fix
  3. Attempt 3: If still failing β€” Claude Opus escalation with full error context

Deploy & Verify

Baremetal flow

For type: "bare-metal" boards:

  1. Code compiles in cloud sandbox (Docker + QEMU verification)
  2. Binary downloads to agent
  3. pyOCD flashes to board memory
  4. UART monitored for output
  5. Output compared against expected pattern

SBC / SSH flow

For type: "sbc" boards with SSH:

  1. Code compiles + runs in cloud sandbox
  2. If sandbox passes β†’ binary SCP'd to target
  3. SSH executes binary on target
  4. stdout captured for verification

Localhost flow

For connection: "localhost":

  1. Code compiles + runs in cloud sandbox
  2. Binary downloaded to ~/respcode-deploy/
  3. Executed directly on local machine
  4. stdout captured for verification

The agent auto-detects the file type and uses the right interpreter: .py β†’ python3, .js β†’ node, .rb β†’ ruby, ELF β†’ direct execution.

Auto-Update

On every startup, the agent checks https://respcode.com/agent/version.json for new versions. If a newer version is available, it downloads, verifies the SHA-256 checksum, replaces itself, and exits with a "please restart" message.

To manually update:

$ curl -fsSL https://respcode.com/agent/install.sh | sh

Troubleshooting

pyOCD not detecting my board

SSH connection fails

Compilation fails in sandbox

macOS Gatekeeper warning

$ xattr -d com.apple.quarantine $(which respcode-agent)

"Permission denied" on serial port (Linux)

$ sudo usermod -aG dialout $USER $ sudo usermod -aG plugdev $USER # Log out and back in for changes to take effect

macOS: pyOCD not found after install

On macOS, pip install places binaries in ~/Library/Python/3.XX/bin/ which may not be in your PATH. The agent searches common locations automatically, but if you need to run pyOCD manually:

# Find where pyocd was installed $ python3 -m site --user-base # Add to PATH (add to ~/.zshrc for persistence) $ export PATH="$HOME/Library/Python/3.12/bin:$PATH"

macOS: boards.yaml not created during install

If the install script fails to create the config file, the agent will auto-create a default one on first run with a localhost target. To add boards afterwards, use /boards ssh or /boards add inside the agent.

$ respcode-agent [ok ] Created default config β†’ ~/.config/respcode/boards.yaml [info ] Add boards with: /boards

macOS: Board not detected during install

Ensure your board is plugged in before running the install script. The installer uses system_profiler SPUSBDataType to detect debug probes on macOS. If you plug in the board after installing, just restart the agent β€” it auto-detects new boards on every startup.

Agent shows "Plan: β€”" (empty)

This happens when the plan field hasn't been set for your user account on the server. Contact support or check that the server migration has been applied. The agent still works normally β€” this is a display-only issue.

Uninstall the agent

$ rm -f ~/.local/bin/respcode-agent $ rm -rf ~/.config/respcode # Remove PATH entry from ~/.zshrc or ~/.bashrc if added
πŸ“– More help

Full troubleshooting guide and FAQs: respcode.com/docs#agent-troubleshooting

Examples

Example 1: Bare-metal Ethernet UDP on STM32F767ZI

Flagship Compete mode generating bare-metal Ethernet firmware. 4 models attempt to write a UDP sender using the LAN8742A PHY over RMII β€” direct register access, no HAL. Claude Opus compiles and sends real UDP packets on the wire.

❯ Write a bare metal Ethernet UDP program for STM32F767ZI. The board has a LAN8742A PHY connected via RMII. Configure static IP 192.168.0.200, send a UDP packet to 192.168.0.175 port 9000 every 2 seconds containing "Hello from STM32F767ZI". Blink green LED on each packet sent. Generate firmware for: Write a bare metal Ethernet UDP... [Compete Flagship (29cr)] Proceed? (y/n) y ⟳Attempt 1/3 β€” Compete Flagship (29cr) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ━━━ GENERATE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [cloud ] Compete: flagship tier generating for STM32F767ZI... [cloud ] Models: claude-opus-4-6, gpt-5-2, gemini-3-pro, deepseek-coder [cloud ] gemini-3-pro βœ“ done (281 chunks) [cloud ] gpt-5-2 βœ“ done (11706 chunks) [cloud ] deepseek-coder βœ“ done (6894 chunks) [cloud ] claude-opus-4-6 βœ“ done (3858 chunks) ━━━ COMPILE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [gcc ] claude-opus-4-6 βœ… 7964 bytes (4.1s) [12936tok] [gen:3091] [gcc ] gpt-5-2 ❌ collect2: error: ld returned 1 exit status [10284tok] [gen:3092] β”‚ collect2: error: ld returned 1 exit status [gcc ] gemini-3-pro βœ… 2152 bytes (4.0s) [4979tok] [gen:3093] [gcc ] deepseek-coder ❌ ./main.c:175:12: error: 'GPIO_TypeDef' has no... [5862tok] [gen:3094] β”‚ ./main.c:175:12: error: 'GPIO_TypeDef' has no member named '... [cloud ] Credits remaining: 474 ━━━ DOWNLOAD ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [cloud ] Downloading artifacts for 2 compiled models... [ok ] claude-opus-4-6 [gen:3091] β†’ respcode-output/.../claude-opus-4-6 (7964 bytes) [ok ] gemini-3-pro [gen:3093] β†’ respcode-output/.../gemini-3-pro (2152 bytes) ━━━ FLASH + VERIFY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [cloud ] Flashing by priority: claude-opus-4-6 β†’ gemini-3-pro [cloud ] 1/2: claude-opus-4-6 (7964 bytes) [pyocd ] Loading firmware.bin at 0x08000000 [pyocd ] [========================================] [pyocd ] Erased 32768 bytes (1 sector), programmed 8192 bytes (8 pages) at 9.06 kB/s [uart ] Listening on /dev/ttyACM0 @ 115200... [uart ] [TX] UDP packet #3 sent (64 bytes) -> 192.168.0.175:9000 [uart ] [TX] UDP packet #5 sent (64 bytes) -> 192.168.0.175:9000 [uart ] [INFO] ARP request for us ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [ βœ… ] UART verified in 10.1s Β· claude-opus-4-6 (model 1) Β· 7964 bytes [ πŸ‘ ] Confirm hardware behavior on your board ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ━━━ RESULT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ βœ… claude-opus-4-6 UART βœ… HW βœ… 7964 bytes ← WINNER ⏭ gemini-3-pro 2152 bytes (not tested β€” winner found) Flash another compiled binary? [1] gemini-3-pro 2152B [n] done
πŸ’‘ What happened

This is a hard prompt β€” bare-metal Ethernet with RMII PHY initialization, MAC DMA descriptors, ARP handling, and UDP packet construction, all without any SDK. Only Claude Opus and Gemini compiled. Claude's firmware sent real UDP packets on the wire at 192.168.0.175:9000 and responded to ARP requests β€” verified via UART output on the Nucleo-F767ZI board.

Example 2: Memory bandwidth test on ARM64 cloud instance

Running 4 open-source models in Compete mode on a remote ARM64 instance via SSH. Each model generates a C program that measures memcpy bandwidth on a 64MB buffer.

❯ write a C program that measures memory bandwidth using memcpy on a 64MB buffer, report read/write speeds in MB/s Generate firmware for: write a C program that measures memory... [Compete Open Source (8cr)] Proceed? (y/n) y ━━━ GENERATE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [cloud ] Compete: open tier generating for ARM64 cloud instance... [cloud ] Models: llama-4-maverick, qwen-3-32b, deepseek-coder, gpt-oss-120b [cloud ] llama-4-maverick βœ“ done (323 chunks) [cloud ] gpt-oss-120b βœ“ done (686 chunks) [cloud ] qwen-3-32b βœ“ done (6092 chunks) [cloud ] deepseek-coder βœ“ done (1105 chunks) ━━━ COMPILE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [gcc ] llama-4-maverick βœ… compiled (2.1s) [961tok] [gen:3024] [gcc ] qwen-3-32b βœ… compiled (4.3s) [7804tok] [gen:3025] [gcc ] deepseek-coder βœ… compiled (3.2s) [1778tok] [gen:3026] [gcc ] gpt-oss-120b βœ… compiled (3.2s) [1344tok] [gen:3027] [cloud ] Credits remaining: 98 ━━━ SANDBOX RESULTS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ βœ… llama-4-maverick exit 0 Β· "Read/Write bandwidth: -18666666666.67 MB/s" βœ… qwen-3-32b exit 0 Β· "Read Speed: 3317.57 MB/s" βœ… deepseek-coder exit 0 Β· "Initializing 64MB buffer..." βœ… gpt-oss-120b exit 0 Β· "Copy (read+write) bandwidth: 4022.29 MB/s" ━━━ DEPLOY TO SBC? ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Target: ubuntu@234.222.211.115 (ARM64 cloud instance) ❯ a # deploy all [scp ] Copied 639760 bytes to 234.222.211.115:/tmp/respcode-test [ssh ] Read Speed: 3927.29 MB/s [ssh ] Write Speed: 3927.29 MB/s [ok ] βœ… qwen-3-32b verified on ARM64 cloud instance [scp ] Copied 640048 bytes to 234.222.211.115:/tmp/respcode-test [ssh ] Buffer size: 64 MB [ssh ] Write bandwidth: 3059.83 MB/s [ssh ] Read bandwidth: 4041.88 MB/s [ssh ] Verification: PASSED [ok ] βœ… deepseek-coder verified on ARM64 cloud instance ━━━ FINAL REPORT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Total time: 67.8s across 1 attempt(s) [cloud ] Credits consumed: 8 total βœ… 4/4 sandbox Β· 4 deployed to SBC
πŸ’‘ What happened

All 4 open-source models compiled successfully in the cloud sandbox. After deploying to real ARM64 hardware, the results diverged β€” Llama had a timer bug (negative bandwidth), while DeepSeek produced the most detailed and accurate output. This is exactly why multi-model comparison matters.

Example 3: Baremetal LED blink and UART initialization on NXP LPC55S69-EVK

Compete mode with 4 models generating bare-metal firmware. The agent enriches the prompt with register-level SVD data (5 peripherals, 227 registers, 64 pins) for the LPC55S69 MCU β€” ensuring models use correct register addresses instead of guessing.

❯ blink the green LED and print hello on UART Generate firmware for: blink the green LED... [Compete Flagship (29cr)] Proceed? (y/n) y ━━━ GENERATE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [cloud ] Compete: flagship tier generating for LPC55S69-EVK... [cloud ] Prompt enriched with SVD register data (808 enums) [cloud ] Models: claude-opus-4-6, gpt-5-2, gemini-3-pro, deepseek-coder [cloud ] claude-opus-4-6 βœ“ done [cloud ] gpt-5-2 βœ“ done [cloud ] gemini-3-pro βœ“ done [cloud ] deepseek-coder βœ“ done ━━━ COMPILE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [gcc ] claude-opus-4-6 βœ… compiled (1.2s) [gen:2801] [gcc ] gpt-5-2 ❌ USART0_FIFOCFG undeclared [gcc ] gemini-3-pro βœ… compiled (0.8s) [gen:2803] [gcc ] deepseek-coder βœ… compiled (0.9s) [gen:2804] ━━━ FLASH + VERIFY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [cloud ] 3 compiled Β· flashing first: Gemini 3 Pro (892 bytes) [pyocd ] Erasing sector 0 (0x00000000 - 0x00007fff) [pyocd ] Programmed 892 bytes at 0x00000000 in 0.04s [pyocd ] Verified βœ… Β· Reset target [uart ] Listening on /dev/ttyACM1 @ 115200... [uart ] Hello from RespCode! [uart ] LED initialized on PIO1_4 [uart ] Blinking... [ok ] βœ… gemini-3-pro verified on LPC55S69-EVK (UART output confirmed) [ πŸ‘ ] Confirm LED is blinking on your board

Example 4: Hello World locally on x86

The simplest test β€” generate a C program and run it directly on your machine. No hardware needed.

❯ hello world in c Generate firmware for: hello world in c [Compete Flagship (29cr)] Proceed? (y/n) y ━━━ COMPILE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [gcc ] claude-opus-4-6 βœ… compiled (0.0s) [gen:3110] [gcc ] gpt-5-2 βœ… compiled (0.0s) [gen:3111] [gcc ] gemini-3-pro βœ… compiled (0.0s) [gen:3112] [gcc ] deepseek-coder βœ… compiled (0.0s) [gen:3113] ━━━ SANDBOX RESULTS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ βœ… claude-opus-4-6 exit 0 Β· "Hello, World!" βœ… gpt-5-2 exit 0 Β· "Hello, world!" βœ… gemini-3-pro exit 0 Β· "Hello, World!" βœ… deepseek-coder exit 0 Β· "hello world" ━━━ DEPLOY LOCALLY? ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ❯ a # deploy all locally [local ] program β†’ ~/respcode-deploy/program (15960 bytes) [run ] Hello, World! [ok ] βœ… claude-opus-4-6 verified locally [local ] program β†’ ~/respcode-deploy/program (15960 bytes) [run ] Hello, world! [ok ] βœ… gpt-5-2 verified locally ━━━ FINAL REPORT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Total time: 26.3s Β· Credits consumed: 29 βœ… 4/4 sandbox Β· 4 deployed locally

Web Platform

Browser-based multi-model code generation and verification. Free & unlimited.

The web platform at respcode.com provides the full RespCode experience in your browser β€” write prompts, select AI models, choose an architecture, and watch code generate in real time with sandbox verification. The web IDE is completely free with unlimited generations.

Orchestration Modes

RespCode offers three ways to orchestrate AI models:

βš”οΈ Compete

Run 2–5 models in parallel. Compare outputs side-by-side. Each gets independent sandbox verification. Best for: exploring different approaches.

πŸ”— Collaborate

Chain models sequentially β€” each refines the previous output. Best for: complex projects needing iterative improvement.

βœ… Consensus

Models vote on the best approach, then a merger model synthesizes the final solution. Best for: production and safety-critical code.

Supported Architectures

ArchitectureToolchainSandboxUse Case
x86_64GCC 13, Clang 17DaytonaDesktop, server, algorithms
ARM64 (AArch64)aarch64-linux-gnu-gccFirecracker on GravitonApple Silicon, Raspberry Pi, cloud instances
ARM32 (ARMv7)arm-linux-gnueabihf-gccFirecracker (AArch32 mode)Embedded Linux, 32-bit SBCs
ARM32 Baremetalarm-none-eabi-gcc + QEMUDocker + QEMU emulationSTM32, NXP, Nordic nRF, RP2040, TI firmware
RISC-V Coming Soonriscv64-linux-gnu-gccβ€”Open ISA development (temporarily disabled)
FPGA / HDL Coming SoonIcarus Verilog, Verilatorβ€”Verilog, VHDL design (temporarily disabled)
PythonPython 3.11Sandboxed interpreterScripts, automation, ML

AI Models

11 models available from 5 providers:

ProviderModels
Anthropicclaude-opus-4-6, claude-sonnet-4-6, claude-haiku-4-5
OpenAIgpt-5-2, gpt-4o-mini
DeepSeekdeepseek-v3, deepseek-coder
Googlegemini-3-pro, gemini-2-flash
Open Sourcellama-4-maverick, qwen-3-32b

Sandbox Execution

Every code generation is compiled and executed in an isolated sandbox. ARM code runs in Firecracker microVMs on Graviton instances; x86 code runs in Daytona containers. The sandbox provides:


VS Code Extension

Multi-model code generation directly in your editor. Coming Soon

🚧 Under Development

The VS Code extension is currently in development. It will allow you to select models, generate code, compare outputs, and run sandbox verification β€” all from within VS Code.

Planned features:


MCP Server

Connect RespCode to Claude Desktop, Cursor, and MCP clients. Coming Soon

🚧 Under Development

The MCP (Model Context Protocol) server will expose RespCode's multi-model generation and sandbox verification as tools that Claude Desktop, Cursor, and other MCP-compatible AI clients can invoke.

Planned tools:


API Reference

The RespCode API powers all clients (web, agent, VS Code, MCP). Base URL: https://respcode.com/api

EndpointMethodDescription
/userGETGet user info, plan, credits
/generatePOST (SSE)Stream multi-model code generation
/artifacts/{gen_id}GETList compiled artifacts
/artifacts/{gen_id}/{art_id}/downloadGETDownload binary artifact
/agent/version.jsonGETCheck for agent updates

All endpoints require Authorization: Bearer <api_key> header (except version check).

Credits & Pricing

TierCredits per generationModels included
Flagship29Claude Opus, GPT-5, Gemini 3 Pro, DeepSeek Coder
Mid17Claude Sonnet, GPT-4o, Gemini Flash, DeepSeek V3
Open Source8Llama 4, Qwen 3, DeepSeek, Mistral
Budget6Claude Haiku, GPT-4o Mini, Gemini Flash

Web platform is free with unlimited generations. Agent & API users get 500 free credits. Upgrade to Pro (29/mo) or Max ($49/mo) for more.