Qwen3.6 35B-A3B: Price, Context, Benchmarks, and Release Details
56.3
SI Score (method si-v3-retained-evidence-2)
37% confidence 37 percent, Low confidence — 2 of 7 expected sources in
Coverage 30% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 73.4
Math (weight 15 percent) 38.6
Preference (weight 15 percent) —
Reasoning (weight 30 percent) 84.3
Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.
Facts
- Input price / 1M
- $0.25Alibaba Model Studio pricingOfficial Alibaba Model Studio Global USD on-demand API; 0<Token≤256K; . 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 price / 1M
- $1.49Alibaba Model Studio pricingOfficial Alibaba Model Studio Global USD on-demand API; 0<Token≤256K; . 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
- 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
- Apr 17, 2026models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Open weights
- Yesmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- text, image, video, audiomodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
Benchmark results
7 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| frontiermath tiers 1 3 v2 | 17.5%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 29, 2026
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 17.5 | math |
| frontiermath tiers 1 3 v2 | 20.4%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 30, 2026
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 20.4 | math |
| gpqa diamond | 83.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 7, 2026
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 83.8 | reasoning |
| gpqa diamond | 84.8%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 7, 2026
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 84.8 | reasoning |
| otis mock aime 2024 2025 | 86.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Aug 7, 2026
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 86.7 | math |
| otis mock aime 2024 2025 | 68.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 7, 2026
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 68.9 | math |
| swe bench verified | 73.4%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 ↗ | 73.4 | coding |
Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.
Sources: in and pending
in Reported (2)
- Epoch AI Benchmarking · arrived Oct 8, 2026
- Official model cards via models.dev · arrived Oct 8, 2026
pending Awaiting (5)
- ARC Prize · carries 13% of expected weight
- Humanity’s Last Exam · carries 13% of expected weight
- LiveBench · carries 13% of expected weight
- LMArena / Arena · carries 25% of expected weight
- Terminal-Bench · carries 6% of expected weight
The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.