Tencent, released Jul 6, 2026

Hy3price, context, benchmarks and release details

Provisional: not enough results to rank yet Open weights 88% confidence 88 percent, High confidence, 2 of 3 expected sources in
60.7
SI Score
#61 of 142 ranked models
Input, per 1M tokens
$0.00models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://cloud.tencent.com/document/product/1823/130050. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; tencent-tokenhub/hy3 Retrieved Oct 9, 2026 · MIT
Open source ↗
Output, per 1M tokens
$0.00models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://cloud.tencent.com/document/product/1823/130050. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; tencent-tokenhub/hy3 Retrieved Oct 9, 2026 · MIT
Open source ↗
Context window
256Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
128Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
Jul 6, 2026models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

How the score breaks down

Coding (weight 40 percent) 69.2
Math (weight 15 percent) —
Preference (weight 15 percent) 76.7
Reasoning (weight 30 percent) 54.2

Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 05:13 UTC.

Around it on the leaderboard

  1. 59 Nemotron 3 Ultra 550B A55B 61.2
  2. 60 DeepSeek V4 Flash 0731 61.0
  3. 61 Hy3 60.7
  4. 62 Claude Haiku 4.5 60.5
  5. 63 Qwen3.5 Flash 59.5

Full leaderboard

Benchmark results

7 benchmarks, 7 results

Each row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.

GPQA Diamondreasoning 90.4%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] highest reasoning effort Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
90.4
Humanity's Last Exam (text only, with tools)reasoning 53.2%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] highest reasoning effort; with tools; text-only Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
53.2
Humanity's Last Exam (text only)reasoning 37%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] highest reasoning effort; without tools; text-only Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
37.0
SWE-bench Procoding 57.9%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] highest reasoning effort; SWE-agent Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
57.9
SWE-bench Verifiedcoding 78%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant] Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
78.0
Terminal-Bench 2.1coding 71.7%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] highest reasoning effort; 4h timeout; 500 episodes; Terminus 2; 2.1 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
71.7
LMArena Textpreference 1438.8 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗
76.7

Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.

Details and sources

Open weights
Yesmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
textmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
70% of expected source weight

Reported (2)

  • Official model cards via models.devOct 8, 2026
  • LMArena / ArenaOct 8, 2026

Awaiting (1)

  • LiveBench30% of weight

Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.

What changed

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