# Kat Dev

Model id on AIHubMix: `kat-dev`
Create an API key: https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms

> KAT-Dev (32B) is an open-source 32B parameter model specifically designed for software engineering tasks. It achieved a 62.4% resolution rate on the SWE-Bench Verified benchmark, ranking fifth among all open-source models of various scales. The model is optimized through multiple stages, including intermediate training, supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT), as well as large-scale agent reinforcement learning (RL). Based on Qwen3-32B, its training process lays the foundation for subsequent fine-tuning and reinforcement learning stages by enhancing fundamental abilities such as tool usage, multi-turn interaction, and instruction following. During the fine-tuning phase, the model not only learns eight carefully curated task types and programming scenarios but also innovatively introduces a reinforcement fine-tuning (RFT) stage guided by human engineer-annotated “teacher trajectories.” The final agent reinforcement learning phase addresses scalability challenges through multi-level prefix caching, entropy-based trajectory pruning, and efficient architecture.

> Capability flags (tool use, structured output, vision, reasoning, …) are **not published** for this model. AIHubMix lists them only after official confirmation and this id is not covered yet — their absence below means unverified, not unsupported. Everything else here comes from the live catalog. Verify with a minimal real call before relying on a capability (see https://aihubmix.com/agents.md — an HTTP 200 alone is not success).

- Developer: Qwen
- Context window: 128,000 tokens
- Input modalities: text
- Pricing: $0.137/M input tokens, $0.548/M output tokens

## Endpoints (base URL: https://aihubmix.com)

- `POST /v1/chat/completions` — OpenAI Chat Completions (`Authorization: Bearer $AIHUBMIX_API_KEY`)

## Example

```bash
curl -s https://aihubmix.com/v1/chat/completions \
  -H "Authorization: Bearer $AIHUBMIX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"kat-dev","messages":[{"role":"user","content":"Hello"}]}'
```

## Response

Without `stream`, `/v1/chat/completions` returns a standard Chat Completions object:

```json
{"id":"...","object":"chat.completion","model":"kat-dev","choices":[{"message":{"role":"assistant","content":"..."}}],"usage":{"prompt_tokens":12,"completion_tokens":24,"total_tokens":36}}
```

With `"stream": true` the response is `text/event-stream`: read each `data:` JSON chunk until `data: [DONE]`. The Messages and Gemini endpoints return their protocols' native response shapes (Anthropic / Google).

## Errors

Error responses carry a `tid` (trace id) — include it when contacting support. Reference: https://docs.aihubmix.com/en/FAQs/HTTP-Codes.md

- 400 — parameter error; most are passed through from the upstream provider (media: `prompt_missing`, `size_not_supported`, `n_not_within_range`, …)
- 401 — missing `Authorization` header, or the key is invalid/expired
- 403 — `insufficient_user_quota` (top up at https://console.aihubmix.com/?utm_source=llms-agent&utm_medium=model-llms), account suspended, or this key is not allowed to use this model
- 429 — rate limited; back off and retry
- 503 — no channel can serve the request (check the model id and your access), or the upstream provider is throttling; retry later

## More

- Model page: https://aihubmix.com/model/kat-dev
- Try in browser: https://playground.aihubmix.com/?model=kat-dev
- Compare with another model (human-facing, side-by-side specs and pricing): https://aihubmix.com/compare — pick this model and a peer there; published pairs are listed in https://aihubmix.com/sitemap-compare.xml, unpublished pairs 404 so do not compose the path by hand
- Full parameter schema: follow `https://aihubmix.com/model-data/index.json` — find this id and fetch its `path` (filenames are content-addressed; do not compose them by hand)
- Generate runnable code programmatically: npm `@aihubmix/codegen` — the generator behind the Playground's "Get Code" (4 protocols × 7 languages, media endpoints included); the body it builds is the exact wire body the Playground sends, so generated snippets and real requests cannot diverge. `@aihubmix/model-schema` (npm) translates the parameter schema above into codegen input
- Site index for agents: https://aihubmix.com/llms.txt · Onboarding: https://aihubmix.com/agents.md

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Canonical version of this document: https://aihubmix.com/model/kat-dev/llms.txt