ZMIME
Comparison · 3 models · Updated Oct 4, 2026

DeepSeek-R1-Distill-Qwen-32B vs Qwen3.5 9B vs QwQ 32B

Qwen3.5 9B comes out ahead, 64 to 52 and 47 on our weighted score, and it is the cheaper option too.

  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. Our pick

    Alibaba (Qwen)

    Qwen3.5 9B

    Released Feb 23, 2026

    64/100
    • ECI139.5
    • Price$0.10 / $0.15
    • Context262K
    Full specs Remove Qwen3.5 9B

  3. Alibaba (Qwen)

    QwQ 32B

    Released Mar 5, 2025

    52/100
    • ECI137.6
    • Price$0.66 / $1.00
    • Context131K
    Full specs Remove QwQ 32B
01 — Verdict

Qwen3.5 9B is our pick

Qwen3.5 9B is the better all-round choice, scoring 64/100 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%.

  • CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · QwQ 32B 137.6 · DeepSeek-R1-Distill-Qwen-32B 137.4
  • Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · QwQ 32B $0.745 per 1M tokens (3:1 blend) · DeepSeek-R1-Distill-Qwen-32B unpriced
  • Longest contextQwen3.5 9BQwen3.5 9B 262,144 · DeepSeek-R1-Distill-Qwen-32B 131,072 · QwQ 32B 131,072 tokens
  • Widest inputsQwen3.5 9BDeepSeek-R1-Distill-Qwen-32B: Text · Qwen3.5 9B: Text, Images, Video · QwQ 32B: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightDeepSeek-R1-Distill-Qwen-32BQwen3.5 9BQwQ 32B
CapabilityCapabilities Index (ECI)67%626562
Inputs & features20%108035
Context window13%243724
Overall100%47/10064/10052/100

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 Qwen3.5 9B vs QwQ 32B specifications side by side
SpecificationDeepSeek-R1-Distill-Qwen-32BDeepSeekQwen3.5 9BAlibaba (Qwen)QwQ 32BAlibaba (Qwen)
Capability
Capabilities Index (ECI)137.4139.5 (best)137.6
ECI rank#110 of 148#101 of 148 (best)#109 of 148
GPQA DiamondGraduate-level science questions64.1%79.0% (best)65.3%
OTIS Mock AIME 2024–2025Competition mathematics55.6%61.7% (best)59.2%
Price per million tokens
Input—$0.10 (best)$0.66
Output—$0.15 (best)$1.00
Cached input———
Blended (3:1)—$0.113 (best)$0.745
Long-context rate—Same rateSame rate
Price source—Median of 14 providersMedian of 1 providers
Limits
Context window131,072 tokens262,144 tokens (best)131,072 tokens
Max output32,768 tokens65,536 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoYesNo
ReasoningYesYesYes
Tool callingNoYesYes
Structured outputNoYesNo
Availability
WeightsOpenOpenOpen
API model ID———
API providers—15 (best)1
ReleasedJan 20, 2025Feb 23, 2026Mar 5, 2025
Knowledge cutoff——Apr 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—
  • Qwen3.5 9B$1.30
  • QwQ 32B$8.60
04 — Questions

Which should you choose?

Which is better: DeepSeek-R1-Distill-Qwen-32B, Qwen3.5 9B or QwQ 32B?

Qwen3.5 9B is the better all-round choice, scoring 64/100 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, Qwen3.5 9B or QwQ 32B?

Qwen3.5 9B is cheaper at $0.10 input / $0.15 output per million tokens (median across 14 API providers). QwQ 32B costs $0.66 input / $1.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.113 per million tokens for Qwen3.5 9B versus $0.745 for QwQ 32B (6.6× as much). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.

Which scores higher on benchmarks?

Qwen3.5 9B scores higher on the Capabilities Index (ECI): Qwen3.5 9B 139.5 (#101 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 (136.5–141.3 vs 133.1–141.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, QwQ 32B 65.3%, DeepSeek-R1-Distill-Qwen-32B 64.1%; OTIS Mock AIME 2024–2025 — Qwen3.5 9B 61.7%, QwQ 32B 59.2%, 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, Qwen3.5 9B and QwQ 32B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 9B 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?

Qwen3.5 9B has the largest context window at 262,144 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, Qwen3.5 9B up to 65,536, QwQ 32B up to 8,192 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-R1-Distill-Qwen-32B accepts text; Qwen3.5 9B accepts text, images and video; QwQ 32B accepts text. Qwen3.5 9B handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights, so you can self-host them.

Which is newer?

Qwen3.5 9B is the newest, released Feb 23, 2026. QwQ 32B came out Mar 5, 2025; DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 2025. Knowledge cutoff: QwQ 32B Apr 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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