Hy3

Tencent Hy reasoning model for coding, instruction following, and agent tasks
- Context
- 262K
- Released
- 3mo ago
- Parameters
- —
- Input / 1M tokens
- $0.08
- Output / 1M tokens
- $0.33
- Cached input / 1M tokens
- $0.02
Sources:models.devOpenRouter
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
No benchmark results have been matched to this model yet.
Specifications
- Developer
- Tencent
- Model family
- Hunyuan
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- July 6, 2026
- Model ID
tencent/hy3- Openness
- Open weights
- License
- —
- Parameters
- —
- Input modalities
- text
- Output modalities
- text
- Modality
- text->text
- Tokenizer
- Other
- Max output tokens
- 128K
- Hugging Face
- tencent/Hy3
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- tencent/hy3
- Source family
- Hy
- Last updated
- 2026-07-06
- Model context
- 256K
- Maximum input
- 192K
- Model output limit
- 128K
- Open weights
- Yes
- File attachments
- No
- Reasoning
- Yes
- Tool calling
- Yes
- Temperature control
- Yes
Downloadable weights
Published benchmarks
| Benchmark | Score | Evaluation details | Evidence |
|---|---|---|---|
| SWE-Bench Verified | 78 · resolved | — | Source |
| SWE-Bench Multilingual | 75.8 · score | SWE-agent · highest reasoning effort | Source |
| SWE-Bench Pro | 57.9 · score | SWE-agent · highest reasoning effort | Source |
| Terminal-Bench | 71.7 · score | Terminus 2 · highest reasoning effort; 4h timeout; 500 episodes · 2.1 | Source |
| NL2Repo | 45.6 · score | Claude Code · highest reasoning effort; 250 turns; 12000s timeout | Source |
| DeepSWE | 28 · score | mini-swe-agent · highest reasoning effort; 2h timeout | Source |
| BrowseComp | 84.2 · score | Tencent internal search harness · highest reasoning effort | Source |
| WideSearch | 76.4 · score | Tencent internal search harness · highest reasoning effort | Source |
| DeepSearchQA | 91 · score | Tencent internal search harness · highest reasoning effort | Source |
| MCP Atlas | 79.1 · score | Scale AI · 500 public tasks · highest reasoning effort; April 2026; 100 tool calls | Source |
| Toolathlon | 48.5 · score | highest reasoning effort | Source |
| APEX-Agents | 25.6 · pass@1 | highest reasoning effort | Source |
| ClawEval | 68.5 · pass@3 | Tencent internal harness · 105 queries · highest reasoning effort · 20260325 | Source |
| WildClawBench | 53.6 · score | OpenClaw · 35 text-only tasks · highest reasoning effort | Source |
| SkillsBench | 55.3 · average over 3 runs | Claude Code · 79 text-only tasks · highest reasoning effort | Source |
| Humanity's Last Exam | 53.2 · score | text-only · highest reasoning effort; with tools | Source |
| Humanity's Last Exam | 37 · score | text-only · highest reasoning effort; without tools | Source |
| GPQA Diamond | 90.4 · score | highest reasoning effort | Source |
| FrontierScience | 21.3 · score | highest reasoning effort; research | Source |
| FrontierScience | 74.8 · score | highest reasoning effort; olympiad | Source |
| USAMO | 72 · score | highest reasoning effort · 2026 | Source |
| MathArena Apex | 38.7 · score | highest reasoning effort | Source |
| ArxivMath | 52.2 · score | highest reasoning effort | Source |
| HorizonMath | 7.1 · pass@12 | highest reasoning effort | Source |
| PHYBench | 77.4 · score | highest reasoning effort | Source |
| CMT Benchmark | 37.8 · score | highest reasoning effort | Source |
| IMOAnswerBench | 90 · score | highest reasoning effort | Source |
| SuperChem | 54.9 · score | highest reasoning effort | Source |
| CL-bench | 23.8 · score | highest reasoning effort | Source |
| CL-bench-life | 17 · score | highest reasoning effort | Source |
| AA-LCR | 73.4 · score | highest reasoning effort | Source |
Complete source record (JSON)
{
"id": "tencent/hy3",
"name": "Hy3",
"description": "Tencent Hy reasoning model for coding, instruction following, and agent tasks",
"family": "Hy",
"last_updated": "2026-07-06",
"attachment": false,
"reasoning": true,
"tool_call": true,
"temperature": true,
"modalities": {
"input": [
"text"
],
"output": [
"text"
]
},
"limit": {
"context": 256000,
"input": 192000,
"output": 128000
},
"benchmarks": [
{
"name": "SWE-Bench Verified",
"score": 78,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "resolved"
},
{
"name": "SWE-Bench Multilingual",
"score": 75.8,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "SWE-agent",
"variant": "highest reasoning effort"
},
{
"name": "SWE-Bench Pro",
"score": 57.9,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "SWE-agent",
"variant": "highest reasoning effort"
},
{
"name": "Terminal-Bench",
"score": 71.7,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "Terminus 2",
"variant": "highest reasoning effort; 4h timeout; 500 episodes",
"version": "2.1"
},
{
"name": "NL2Repo",
"score": 45.6,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "Claude Code",
"variant": "highest reasoning effort; 250 turns; 12000s timeout"
},
{
"name": "DeepSWE",
"score": 28,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "mini-swe-agent",
"variant": "highest reasoning effort; 2h timeout"
},
{
"name": "BrowseComp",
"score": 84.2,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "Tencent internal search harness",
"variant": "highest reasoning effort"
},
{
"name": "WideSearch",
"score": 76.4,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "Tencent internal search harness",
"variant": "highest reasoning effort"
},
{
"name": "DeepSearchQA",
"score": 91,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "Tencent internal search harness",
"variant": "highest reasoning effort"
},
{
"name": "MCP Atlas",
"score": 79.1,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "Scale AI",
"variant": "highest reasoning effort; April 2026; 100 tool calls",
"dataset": "500 public tasks"
},
{
"name": "Toolathlon",
"score": 48.5,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "APEX-Agents",
"score": 25.6,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "pass@1",
"variant": "highest reasoning effort"
},
{
"name": "ClawEval",
"score": 68.5,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "pass@3",
"harness": "Tencent internal harness",
"variant": "highest reasoning effort",
"dataset": "105 queries",
"version": "20260325"
},
{
"name": "WildClawBench",
"score": 53.6,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"harness": "OpenClaw",
"variant": "highest reasoning effort",
"dataset": "35 text-only tasks"
},
{
"name": "SkillsBench",
"score": 55.3,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "average over 3 runs",
"harness": "Claude Code",
"variant": "highest reasoning effort",
"dataset": "79 text-only tasks"
},
{
"name": "Humanity's Last Exam",
"score": 53.2,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort; with tools",
"dataset": "text-only"
},
{
"name": "Humanity's Last Exam",
"score": 37,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort; without tools",
"dataset": "text-only"
},
{
"name": "GPQA Diamond",
"score": 90.4,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "FrontierScience",
"score": 21.3,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort; research"
},
{
"name": "FrontierScience",
"score": 74.8,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort; olympiad"
},
{
"name": "USAMO",
"score": 72,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort",
"version": "2026"
},
{
"name": "MathArena Apex",
"score": 38.7,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "ArxivMath",
"score": 52.2,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "HorizonMath",
"score": 7.1,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "pass@12",
"variant": "highest reasoning effort"
},
{
"name": "PHYBench",
"score": 77.4,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "CMT Benchmark",
"score": 37.8,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "IMOAnswerBench",
"score": 90,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "SuperChem",
"score": 54.9,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "CL-bench",
"score": 23.8,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "CL-bench-life",
"score": 17,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
},
{
"name": "AA-LCR",
"score": 73.4,
"source": "https://huggingface.co/tencent/Hy3",
"metric": "score",
"variant": "highest reasoning effort"
}
],
"release_date": "2026-07-06",
"open_weights": true,
"weights": [
{
"label": "Hugging Face",
"url": "https://huggingface.co/tencent/Hy3"
}
]
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| tencent/fp8 | 262K | $0.13 | $0.53 | $0.03 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| gmicloud/bf16 | 262K | $0.14 | $0.58 | $0.04 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| novita | 262K | $0.14 | $0.58 | $0.04 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| phala | 262K | $0.15 | $0.64 | $0.04 | — | 99.78% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| atlas-cloud/fp8 | 262K | $0.20 | $0.80 | $0.05 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 |
Provider data:OpenRouter
Deployment graph
Can I run this?
Vertical Tabs only shows compatibility when it has structured evidence tying this exact model to hardware, runtime, quantization, memory use, and observed performance.