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Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-R1-Distill-Qwen-32B vs QwQ 32B vs Claude Sonnet 3.7

Claude Sonnet 3.7 comes out ahead, 63 to 52 and 47 on our weighted score, though QwQ 32B is 8.1× cheaper per token.

  1. DeepSeek

    DeepSeek-R1-Distill-Qwen-32B

    Released Jan 20, 2025

    47/100
    • ECI137.4
    • Price—
    • Context131K
    Full specs Remove DeepSeek-R1-Distill-Qwen-32B

  2. Alibaba (Qwen)

    QwQ 32B

    Released Mar 5, 2025

    52/100
    • ECI137.6
    • Price$0.66 / $1.00
    • Context131K
    Full specs Remove QwQ 32B
  3. Our pick

    Anthropic

    Claude Sonnet 3.7

    Released Feb 19, 2025

    63/100
    • ECI141.2
    • Price$3.00 / $15.00
    • Context200K
    Full specs Remove Claude Sonnet 3.7
01 — Verdict

Claude Sonnet 3.7 is our pick

Claude Sonnet 3.7 is the better all-round choice, scoring 63/100 against QwQ 32B (52) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.

  • CapabilityClaude Sonnet 3.7Capabilities Index (ECI): Claude Sonnet 3.7 141.2 · QwQ 32B 137.6 · DeepSeek-R1-Distill-Qwen-32B 137.4
  • Lowest priceQwQ 32BQwQ 32B $0.745 · Claude Sonnet 3.7 $6.00 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
  • Longest contextClaude Sonnet 3.7Claude Sonnet 3.7 200,000 · DeepSeek-R1-Distill-Qwen-32B 131,072 · QwQ 32B 131,072 tokens
  • Widest inputsClaude Sonnet 3.7DeepSeek-R1-Distill-Qwen-32B: Text · QwQ 32B: Text · Claude Sonnet 3.7: Text, Images, PDFs
  • Self-hostingDeepSeek-R1-Distill-Qwen-32B and QwQ 32BPublishes downloadable weights
How the score is built
MeasureWeightDeepSeek-R1-Distill-Qwen-32BQwQ 32BClaude Sonnet 3.7
CapabilityCapabilities Index (ECI)67%626267
Inputs & features20%103570
Context window13%242432
Overall100%47/10052/10063/100

Left out because at least one model lacks the data: price. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

DeepSeek-R1-Distill-Qwen-32B vs QwQ 32B vs Claude Sonnet 3.7 specifications side by side
SpecificationDeepSeek-R1-Distill-Qwen-32BDeepSeekQwQ 32BAlibaba (Qwen)Claude Sonnet 3.7Anthropic
Capability
Capabilities Index (ECI)137.4137.6141.2 (best)
ECI rank#110 of 148#109 of 148#96 of 148 (best)
GPQA DiamondGraduate-level science questions64.1%65.3%79.7% (best)
OTIS Mock AIME 2024–2025Competition mathematics55.6%59.2% (best)57.8%
SWE-bench VerifiedFixing real GitHub issues——61.0%
Price per million tokens
Input—$0.66 (best)$3.00
Output—$1.00 (best)$15.00
Cached input———
Blended (3:1)—$0.745 (best)$6.00
Long-context rate—Same rateSame rate
Price source—Median of 1 providersMedian of 3 providers
Limits
Context window131,072 tokens131,072 tokens200,000 tokens (best)
Max output32,768 tokens8,192 tokens64,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingNoYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenProprietary
API model ID———
API providers—13 (best)
ReleasedJan 20, 2025Mar 5, 2025Feb 19, 2025
Knowledge cutoff—Apr 2024Oct 31, 2024
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.

  • DeepSeek-R1-Distill-Qwen-32B—
  • QwQ 32B$8.60
  • Claude Sonnet 3.7$60.00
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1-Distill-Qwen-32B, QwQ 32B or Claude Sonnet 3.7?

Claude Sonnet 3.7 is the better all-round choice, scoring 63/100 against QwQ 32B (52) and DeepSeek-R1-Distill-Qwen-32B (47). It leads on capability, inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.

Which is cheaper, DeepSeek-R1-Distill-Qwen-32B, QwQ 32B or Claude Sonnet 3.7?

QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). Claude Sonnet 3.7 costs $3.00 input / $15.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for QwQ 32B versus $6.00 for Claude Sonnet 3.7 (8.1× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.

Which scores higher on benchmarks?

Claude Sonnet 3.7 scores higher on the Capabilities Index (ECI): Claude Sonnet 3.7 141.2 (#96 of 148), QwQ 32B 137.6 (#109 of 148) and DeepSeek-R1-Distill-Qwen-32B 137.4 (#110 of 148). The confidence ranges of the top two overlap (138.7–142.9 vs 133.1–141.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Claude Sonnet 3.7 79.7%, QwQ 32B 65.3%, DeepSeek-R1-Distill-Qwen-32B 64.1%; OTIS Mock AIME 2024–2025 — QwQ 32B 59.2%, Claude Sonnet 3.7 57.8%, DeepSeek-R1-Distill-Qwen-32B 55.6%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-R1-Distill-Qwen-32B and QwQ 32B yet, so there is no like-for-like coding score. On overall capability, Claude Sonnet 3.7 leads, which tends to carry over to coding, but test on your own codebase. Note that DeepSeek-R1-Distill-Qwen-32B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Claude Sonnet 3.7 has the largest context window at 200,000 tokens, against 131,072 for DeepSeek-R1-Distill-Qwen-32B and 131,072 for QwQ 32B. Maximum output per response: DeepSeek-R1-Distill-Qwen-32B up to 32,768, QwQ 32B up to 8,192, Claude Sonnet 3.7 up to 64,000 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-R1-Distill-Qwen-32B accepts text; QwQ 32B accepts text; Claude Sonnet 3.7 accepts text, images and PDFs. Claude Sonnet 3.7 handles the widest range of inputs.

Are any of these open source?

DeepSeek-R1-Distill-Qwen-32B and QwQ 32B publishes its weights and can be self-hosted; Claude Sonnet 3.7 is proprietary.

Which is newer?

QwQ 32B is the newest, released Mar 5, 2025. Claude Sonnet 3.7 came out Feb 19, 2025; DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025. Knowledge cutoff: QwQ 32B Apr 2024, Claude Sonnet 3.7 Oct 31, 2024.

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 Oct 4, 2026.

05 — Keep comparing

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