Alibaba / Qwen, released Feb 23, 2026
Qwen3.5 9Bprice, context, benchmarks and release details
- Input, per 1M tokens
- not yet reported
- Output, per 1M tokens
- not yet reported
- Context window
- 262Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 65.5Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Feb 23, 2026models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
How the score breaks down
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, 06:15 UTC.
Around it on the leaderboard
- 1 Claude Fable 5.1 80.2
- 2 Claude Opus 5.5 78.4
- 3 GPT-6 Astra 77.5
- 4 Claude Fable 5 76.8
- 5 Claude Opus 5 74.9
Benchmark results
2 benchmarks, 4 resultsEach 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 79.0%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 27, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
79.0 2 settings
- no reasoning 78.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 27, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 2 79.0%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 27, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
OTIS Mock AIME 2024–2025math 61.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 27, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
61.7 2 settings
- no reasoning 61.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 27, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 2 42.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 27, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
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
- text, image, videomodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - First seen by SuperIndex
- Oct 8, 2026
- Coverage
- 25% of expected source weight
Reported (1)
- Epoch AI BenchmarkingOct 8, 2026
Awaiting (6)
- ARC Prize13% of weight
- Humanity’s Last Exam13% of weight
- Official model cards via models.dev4% of weight
- LiveBench13% of weight
- LMArena / Arena25% of weight
- Terminal-Bench6% of weight
Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.