ApertureAug 2026
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Alibaba (Qwen)
Q

Qwen3.8 Flash

Aug 2026 · Open weight · Current · estimated evidence

Qwen’s cheap Fast lane. Use it as the open-weight Luna, not as a Max replacement.

Open compareLab site

Intelligence

50

AA Index

API price

$0.16 / $0.47

Input / output per 1M

Context

1M

90 tok/s

Capability

Intelligence Index50
Coding index64
Agentic index44
Arena Elo (offset)—

Use it when

  • ▸Open-weight volume
  • ▸Batch

Skip if

  • –You need Max-class agents

Benchmarks

GPQA Diamond
Graduate-level science questions designed so Google search is not enough. Still one of the cleanest knowledge/reasoning splits.
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Humanity’s Last Exam
Expert-written questions across fields. Harder than MMLU; the current differentiator for “does this model actually know things.”
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MMLU-Pro
Harder, less-saturated successor to MMLU. Classic MMLU is above 90% for every flagship and no longer ranks the field.
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SWE-bench Verified
500 human-validated GitHub issues. Score swings 5–15 points by harness — treat vendor numbers as an upper bound.
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SWE-bench Pro
Harder, contamination-resistant coding eval. Currently the best public split between “can code” and “can maintain a repo.”
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Terminal-Bench 2.1
End-to-end tasks in a real terminal. Better proxy for coding agents than HumanEval, which is fully saturated.
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ARC-AGI-2
Abstract visual puzzles. Rewards generalization over memorization. GPT-5.6 Sol currently leads the published set.
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AIME 2025
American Invitational Mathematics Examination. Contest math; reasoning-mode models dominate.
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MMMU
College-level multimodal understanding across diagrams, charts, and exam figures.
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Modalities

text · vision · tools

Reasoning mode

hybrid

Hybrid and reasoning models spend tokens thinking. That raises GPQA and agents, and also raises latency and bill.

Close on intelligence

  • OGPT-5.6 Luna52.3
  • GGemini 3.1 Pro47.7
  • QQwen3.8 27B52

Same lab

  • Qwen3.8 Max
  • Qwen3.8 27B

Aperture is a field guide, not a vendor. Scores compiled 28 Aug 2026.

MethodologyHow to pick