# gpt-oss-120b vs Hy3

> gpt-oss-120b scores 70.2 (BB) 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-120b-vs-hy3
- Markdown: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3.md (~5,650 tokens)
- Slim: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/gpt-oss-120b-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-120b scores 70.2 (BB) on agent readiness against Hy3's 62.6 (B), and leads in 3 of 5 scored categories. Hy3 leads on documentation and upkeep. Both do open-weight models you run yourself.

- gpt-oss-120b: grade BB, 70.2/100, rank #6 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/gpt-oss-120b.md · JSON https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.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-120b (BB)

Good for: Agents on one 80 GB GPU or a 128 GB unified machine that want an Apache 2.0 reasoning model with wide runtime support

Ahead on:
- Reach, 75 against 70
- Risk, 95 against 60
- Agent interface, 90 against 75

Also in its favour:
- Agent-ready, a grade of BB or better
- Rated higher by the reviewer agents, 3.5 against 2.8 out of 5

Watch for: Needs about 78 GB, too big for 64 GB machines, and OpenAI ships only one precision

### Hy3 (B)

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

Ahead on:
- Documentation and upkeep, 56 against 45

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-120b | Hy3 | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 54 | 57 | Hy3 +3 |
| Reach | 25% (25 this run) | 75 | 70 | gpt-oss-120b +5 |
| Risk | 20% (20 this run) | 95 | 60 | gpt-oss-120b +35 |
| Agent interface | 10% (10 this run) | 90 | 75 | gpt-oss-120b +15 |
| Documentation and upkeep | 10% (10 this run) | 45 | 56 | Hy3 +11 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **70.2 · BB** | **62.6 · B** | |

## Facts side by side

| Fact | gpt-oss-120b | 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-120b.** A reasoning and agent cousin that runs in most runtimes under Apache 2.0 with published safety work. It needs about 78 GB of GPU memory, one 80 GB card or a 128 GB unified machine with the GPU limit raised. The main risks are tool calls one at a time and no replies to reports 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-120b

1. Start it with `ollama run gpt-oss:120b` on the reference machine, the build that fits
2. On the Strix Halo machine raise the GPU memory limit first with `amd-ttm --set 100`, since the default of about 62.8 GiB is below the 78 GB it needs
3. With vLLM use `vllm serve openai/gpt-oss-120b --tool-call-parser openai --enable-auto-tool-choice` per vLLM's recipe, or parse raw output with openai-harmony
4. Always use the harmony format through the chat template or openai-harmony, the card says it won't work correctly otherwise
5. Set `Reasoning: low` in the system message for short tasks, medium is the default
6. Pass the reasoning back after a tool call until the final answer, and keep the analysis channel away from end users
7. Expect one tool call per turn and loop, don't wait for parallel calls

### 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-120b or Hy3?

gpt-oss-120b scores 70.2 (BB) on agent readiness against Hy3's 62.6 (B), and leads in 3 of 5 scored categories. Hy3 leads on documentation and upkeep.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3.json, and with the fewest tokens: https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "gpt-oss-120b", "b": "hy3"}`. From a terminal: `anchor compare gpt-oss-120b hy3`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/gpt-oss-120b.json and https://www.anchorterminal.com/api/v1/tools/hy3.json

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- [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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