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Comparison · 2 models · Updated Nov 2, 2026

Qwen3.8 27B vs GPT-6 Astra

Too close to call on our weighted score (GPT-6 Astra 68, Qwen3.8 27B 66). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen3.8 27B

    Released Aug 14, 2026

    66/100
    • ECI151.8
    • Price$0.40 / $2.55
    • Context262K
    Full specs Remove Qwen3.8 27B

  2. OpenAI

    GPT-6 Astra

    Released Sep 4, 2026New

    68/100
    • ECI169.1
    • Price$10.00 / $50.00
    • Context1.05M
    Full specs Remove GPT-6 Astra

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GPT-6 Astra 68/100, Qwen3.8 27B 66/100), so choose by what matters most for your work: GPT-6 Astra for raw capability and Qwen3.8 27B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-6 AstraCapabilities Index (ECI): GPT-6 Astra 169.1 · Qwen3.8 27B 151.8
  • Lowest priceQwen3.8 27BQwen3.8 27B $0.938 · GPT-6 Astra $20.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-6 AstraGPT-6 Astra 1,050,000 · Qwen3.8 27B 262,144 tokens
  • Widest inputsSame inputsQwen3.8 27B: Text, Images, Video · GPT-6 Astra: Text, Images, PDFs
  • Self-hostingQwen3.8 27BPublishes downloadable weights
How the score is built
MeasureWeightQwen3.8 27BGPT-6 Astra
CapabilityCapabilities Index (ECI)50%79100
Price25%490
Inputs & features15%7080
Context window10%3761
Overall100%66/10068/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen3.8 27B vs GPT-6 Astra specifications side by side
SpecificationQwen3.8 27BAlibaba (Qwen)GPT-6 AstraOpenAI
Capability
Capabilities Index (ECI)151.8169.1 (best)
ECI rank#54 of 165#1 of 165 (best)
GPQA DiamondGraduate-level science questions—95.8%
FrontierMath Tiers 1–3Research-level mathematics—93.7%
OTIS Mock AIME 2024–2025Competition mathematics—100%
SimpleQA VerifiedShort factual questions—75.6%
Price per million tokens
Input$0.40 (best)$10.00
Output$2.55 (best)$50.00
Cached input—$1.00
Blended (3:1)$0.938 (best)$20.00
Long-context rateSame rateOver 272K: $20.00 / $75.00
Price sourceMedian of 49 providersOfficial OpenAI API
Limits
Context window262,144 tokens1,050,000 tokens (best)
Max output32,768 tokens128,000 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoYes
AudioNoNo
VideoYesNo
ReasoningYesYeslow · medium · high · xhigh · max
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenProprietary
API model ID—gpt-6-astra
API providers53 (best)37
ReleasedAug 14, 2026Sep 4, 2026
Knowledge cutoff—Apr 30, 2026
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Qwen3.8 27B$9.10
  • GPT-6 Astra$200.00
04 — Questions

Which should you choose?

Which is better: Qwen3.8 27B or GPT-6 Astra?

It is close. Our weighted score puts them within 2 points (GPT-6 Astra 68/100, Qwen3.8 27B 66/100), so choose by what matters most for your work: GPT-6 Astra for raw capability and Qwen3.8 27B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3.8 27B or GPT-6 Astra?

Qwen3.8 27B is cheaper at $0.40 input / $2.55 output per million tokens (median across 49 API providers). GPT-6 Astra costs $10.00 input / $50.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.938 per million tokens for Qwen3.8 27B versus $20.00 for GPT-6 Astra (21× as much).

Which scores higher on benchmarks?

GPT-6 Astra scores higher on the Capabilities Index (ECI): GPT-6 Astra 169.1 (#1 of 165) and Qwen3.8 27B 151.8 (#54 of 165). Their confidence ranges do not overlap (165.9–174.3 vs 149.9–153.6), so the gap is a real one.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.8 27B and GPT-6 Astra yet, so there is no like-for-like coding score. On overall capability, GPT-6 Astra leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

GPT-6 Astra has the largest context window at 1,050,000 tokens, against 262,144 for Qwen3.8 27B. Maximum output per response: Qwen3.8 27B up to 32,768, GPT-6 Astra up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Qwen3.8 27B accepts text, images and video; GPT-6 Astra accepts text, images and PDFs. They handle the same number of input types.

Are any of these open source?

Qwen3.8 27B publishes its weights and can be self-hosted; GPT-6 Astra is proprietary.

Which is newer?

GPT-6 Astra is the newest, released Sep 4, 2026. Qwen3.8 27B came out Aug 14, 2026. Knowledge cutoff: GPT-6 Astra Apr 30, 2026.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.

05 — Keep comparing

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