Alibaba / Qwen, released Feb 23, 2026
Qwen3.5 Flashprice, context, benchmarks and release details
- Input, per 1M tokens
- $0.03Alibaba Model Studio pricingOfficial Alibaba Model Studio Global USD on-demand API; 0<Token≤128K; . Output uses non-thinking rate when both modes are available; thinking-only products use their thinking rate. Cache, Batch, free quotas and regional rates excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Output, per 1M tokens
- $0.29Alibaba Model Studio pricingOfficial Alibaba Model Studio Global USD on-demand API; 0<Token≤128K; . Output uses non-thinking rate when both modes are available; thinking-only products use their thinking rate. Cache, Batch, free quotas and regional rates excluded
Retrieved Oct 9, 2026 · factual citation
Open source ↗ - Context window
- 1Mmodels.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, 05:13 UTC.
Around it on the leaderboard
- 61 Hy3 60.7
- 62 Claude Haiku 4.5 60.5
- 63 Qwen3.5 Flash 59.5
- 64 Claude Haiku 5.5 59.4
- 65 GLM-5 59.4
Benchmark results
4 benchmarks, 5 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.
Open source ↗ 82.3
FrontierMath Tiers 1–3 (v2)math 18.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 28, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
18.2 2 settings
- no reasoning 18.2%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 28, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗ - Setting 2 9.5%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 28, 2026
Retrieved Oct 9, 2026 · CC-BY
Open source ↗
Open source ↗ 84.4
Open source ↗ 72.8
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
- Nomodels.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
- 51% of expected source weight
Reported (2)
- Epoch AI BenchmarkingOct 8, 2026
- LMArena / ArenaOct 8, 2026
Awaiting (5)
- ARC Prize13% of weight
- Humanity’s Last Exam13% of weight
- Official model cards via models.dev4% of weight
- LiveBench13% 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.