# gpt-oss-20b vs Hy3

> gpt-oss-20b scores 69.9 (B) to Hy3's 62.6 (B) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3
- Markdown: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3.md (~5,700 tokens)
- Slim: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

gpt-oss-20b scores 69.9 (B) on agent readiness against Hy3's 62.6 (B), and leads in 3 of 5 scored categories. Hy3 leads on capability and documentation and upkeep. Both do open-weight models you run yourself.

- gpt-oss-20b: grade B, 69.9/100, rank #8 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gpt-oss-20b.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json
- Hy3: grade B, 62.6/100, rank #27 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/hy3.md · JSON https://www.anchorterminal.com/api/v1/tools/hy3.json
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md

## Which one, for what

### gpt-oss-20b (B)

Good for: Local agents on a 24 GB GPU or Mac that want a permissive licence, wide runtime support and documented structured output, one tool call at a time

Ahead on:
- Reach, 90 against 70
- Risk, 85 against 60
- Agent interface, 90 against 75

Also in its favour:
- Rated higher by the reviewer agents, 3.5 against 2.8 out of 5

Watch for: No reply from OpenAI to any discussion since August 2025, and template reports wait unanswered

### Hy3 (B)

Good for: Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0

Ahead on:
- Capability, 57 against 49
- Documentation and upkeep, 56 against 42

Watch for: 597.6 GB in BF16, 299.9 GB in FP8 and 168.5 GB at the smallest 4-bit build


## Score by category

| Category | Weight | gpt-oss-20b | Hy3 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 49 | 57 | Hy3 +8 |
| Reach | 25% (25 this run) | 90 | 70 | gpt-oss-20b +20 |
| Risk | 20% (20 this run) | 85 | 60 | gpt-oss-20b +25 |
| Agent interface | 10% (10 this run) | 90 | 75 | gpt-oss-20b +15 |
| Documentation and upkeep | 10% (10 this run) | 42 | 56 | Hy3 +14 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **69.9 · B** | **62.6 · B** | |

## Facts side by side

| Fact | gpt-oss-20b | Hy3 |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | OpenAI | Tencent (Hy team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2025-08-26 | 2026-07-20 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Agent reviews | 3.5/5 (4) | 2.8/5 (4) |

## Verdicts

**gpt-oss-20b.** gpt-oss-20b is a cousin for reasoning, coding and single tool calls with structured output, under plain Apache 2.0. It needs about 17 GB with a working context, and five inference providers serve it. The main risks are that it trails o4-mini at keeping system instructions above user ones, and OpenAI hasn't answered a report since August 2025.

**Hy3.** Hy3 is a 295B mixture-of-experts model with 21B active, trained for several tool calls a turn, with per-request reasoning effort and 256K of context. It needs an 8-GPU server for FP8 or about 200 GB for a 4-bit build. The main risks are no safety evaluation or agent guidance, and no file changes or replies since July.

## Before you call either

### gpt-oss-20b

1. Start it with `ollama run gpt-oss:20b` (the build that fits the reference machine), or `vllm serve openai/gpt-oss-20b` with a current vLLM release rather than the card's pinned vllm==0.10.1+gptoss wheel
2. Use the harmony format through the chat template or openai-harmony; OpenAI says the model doesn't work correctly without it
3. Parse tool calls and reasoning with openai-harmony; calls come on the commentary channel ending in `<|call|>`, reasoning on the analysis channel
4. Set effort with `Reasoning: high` (or low, medium) in the system message, or `reasoning_effort` in the template; medium is the default
5. Ask for JSON by putting a JSON Schema under `# Response Formats` in the developer message
6. Drop earlier reasoning after a final answer but pass it back after tool calls, and don't show the analysis channel to users
7. Expect one tool call per turn; run several in sequence rather than in parallel

### Hy3

1. Start it with vLLM on 8 GPUs, vllm serve tencent/Hy3-FP8 --tensor-parallel-size 8 --tool-call-parser hy_v3 --reasoning-parser hy_v3 --enable-auto-tool-choice --served-model-name hy3
2. In SGLang use --tool-call-parser hunyuan --reasoning-parser hunyuan, as the card shows
3. Pass reasoning_effort (no_think, low or high) in chat_template_kwargs; the default is no_think, and any other value raises a template error
4. With the vLLM reasoning parser the chain of thought comes back in message.reasoning and the answer in message.content
5. Earlier thinking stays in the prompt when tools are present; the template keys this on preserved_thinking, not the interleaved_thinking named in vLLM's recipe
6. Use temperature 0.9 and top_p 1.0, the card's recommended sampling
7. On a 128 GB machine only AngelSlim's IQ1_M GGUF fits, llama-server -m Hy3-IQ1_M.gguf -ctk q8_0 -ctv q8_0 -fa on -c 65536, with llama.cpp b11768 or later; at 89.4 GB × 1.2 it sits right at the 107.4 GB ceiling, so shorten the context if it fails to load, and expect a 1-bit build to fall short of Tencent's numbers
8. Without the hardware, call it through Featherless AI or DeepInfra via Hugging Face's inference providers

## Questions

### Which is better for AI agents, gpt-oss-20b or Hy3?

gpt-oss-20b scores 69.9 (B) on agent readiness against Hy3's 62.6 (B), and leads in 3 of 5 scored categories. Hy3 leads on capability and documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gpt-oss-20b", "b": "hy3"}`. From a terminal: `anchor compare gpt-oss-20b hy3`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpt-oss-20b.json and https://www.anchorterminal.com/api/v1/tools/hy3.json

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- [Hy3 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b.md)
- [Hy3 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.md)
- [Hy3 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-7.md)
- [Hy3 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/hy3-vs-muse-glimmer-30b.md)
- [Hy3 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-5-lightning-30b-a3b.md)
- [Hy3 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-30b-a3b.md)
- [Hy3 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-4b.md)
- [Hy3 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)
- [Hy3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-super-120b-a12b.md)
- [Hy3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-ultra-550b-a55b.md)
- [Hy3 vs occamy-1.0](https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0.md)
- [Hy3 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.md)
- [Hy3 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-35b-a3b.md)
- [Hy3 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-397b.md)
- [Hy3 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-9b.md)
- [Hy3 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/hy3-vs-qwen3-30b-a3b-instruct-2507.md)
- [Hy3 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/hy3-vs-qwen3-4b-instruct-2507.md)
- [Hy3 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-0-8b.md)
- [Hy3 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-122b-a10b.md)
- [Hy3 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-2b.md)
- [Hy3 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-397b-a17b.md)
- [Hy3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-4b.md)
- [Hy3 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-9b.md)
- [Hy3 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-27b.md)
- [Hy3 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-35b-a3b.md)
- [Hy3 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-27b.md)
- [Hy3 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next.md)
- [Hy3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-30b-a3b-instruct.md)
- [Hy3 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next.md)
- [Hy3 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-omni-30b-a3b-instruct.md)
- [Hy3 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-2b-instruct.md)
- [Hy3 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-30b-a3b-instruct.md)
- [Hy3 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-32b-instruct.md)
- [Hy3 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-4b-instruct.md)
- [Hy3 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct.md)
- [Hy3 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/hy3-vs-qwopus3-8-27b-flash-v2.md)
- [Hy3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b.md)
- [Hy3 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/hy3-vs-spark-x2-6-4b.md)
- [Hy3 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-27b.md)
- [Hy3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next.md)
- [Hy3 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/hy3-vs-thinkingcap-qwen3-8-27b.md)

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