SI Index Data as of Oct 9, 2026

Qwen3.6 Flash: Price, Context, Benchmarks, and Release Details

Alibaba / Qwen provisional listing · first seen Oct 8, 2026 · score computed Oct 9, 2026, 01:50 UTC
54.9
SI Score (method si-v3-retained-evidence-2)
32% confidence 32 percent, Low confidence — 1 of 7 expected sources in
Coverage 25% of expected source weight · 100% confidence at 80% coverage

Pillar breakdown

Coding (weight 40 percent) —
Math (weight 15 percent) 41.4
Preference (weight 15 percent) —
Reasoning (weight 30 percent) 83.3

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
$0.17Alibaba 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
$0.99Alibaba 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
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
Apr 27, 2026models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
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 ↗

Benchmark results

4 results
Benchmark Raw result Normalized (0–100) Pillar
frontiermath tiers 1 3 v2 17.2%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 ↗ 		17.2 math
frontiermath tiers 1 3 v2 22.5%Epoch AI BenchmarkingEpoch-owned evaluation mean score; scores only, no benchmark questions [variant] nonePublished Aug 29, 2026 Retrieved Oct 9, 2026 · CC-BY
Open source ↗ 		22.5 math
gpqa diamond 83.3%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 ↗ 		83.3 reasoning
otis mock aime 2024 2025 84.4%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 ↗ 		84.4 math

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 (1)

  • Epoch AI Benchmarking · arrived Oct 8, 2026

pending Awaiting (6)

  • ARC Prize · carries 13% of expected weight
  • Humanity’s Last Exam · carries 13% of expected weight
  • Official model cards via models.dev · carries 4% 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.