Qwen3 235B-A22B: Price, Context, Benchmarks, and Release Details
50.3
SI Score (method si-v3-retained-evidence-2)
#106 of 140 ranked
76% confidence 76 percent, Medium confidence — 4 of 8 expected sources in
Coverage 60% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 21.4
Math (weight 15 percent) 68.9
Preference (weight 15 percent) 69.7
Reasoning (weight 30 percent) 70.7
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
- $0.29Alibaba Model Studio pricingOfficial Alibaba Model Studio Global USD on-demand API; standard tier; Non-Thinking and Thinking modes. 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
- $1.15Alibaba Model Studio pricingOfficial Alibaba Model Studio Global USD on-demand API; standard tier; Non-Thinking and Thinking modes. 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
- 131Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 16.4Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Apr 1, 2025models.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
- textmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
Benchmark results
5 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| gpqa diamond | 70.7%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jun 3, 2025
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 70.7 | reasoning |
| lmarena text | 1366.6 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026
Retrieved Oct 9, 2026 · CC-BY-4.0 Open source ↗ | 69.7 | preference |
| math level 5 | 68.9%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] Published Jun 3, 2025
Retrieved Oct 9, 2026 · CC-BY Open source ↗ | 68.9 | math |
| swe bench pro public | 21.4%Official model cards via models.devLab-reported; metric resolve rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] public
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 21.4 | coding |
| swe bench pro public | 21.4%SWE-bench Pro (public)Published steward score [variant] Published Jan 27, 2026
Retrieved Oct 9, 2026 · factual citation Open source ↗ | 21.4 | 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 (4)
- Epoch AI Benchmarking · arrived Oct 8, 2026
- Official model cards via models.dev · arrived Oct 8, 2026
- LMArena / Arena · arrived Oct 8, 2026
- SWE-bench Pro (public) · arrived Oct 8, 2026
pending Awaiting (4)
- ARC Prize · carries 11% of expected weight
- Humanity’s Last Exam · carries 11% of expected weight
- LiveBench · carries 11% 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.