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Comparison · 3 models · Updated Oct 4, 2026

QwQ 32B vs DeepSeek-V3 vs GPT-4.1 mini

GPT-4.1 mini comes out ahead, 60 to 53 and 50 on our weighted score, though DeepSeek-V3 is 26% cheaper per token.

  1. Alibaba (Qwen)

    QwQ 32B

    Released Mar 5, 2025

    53/100
    • ECI137.6
    • Price$0.66 / $1.00
    • Context131K
    Full specs Remove QwQ 32B

  2. DeepSeek

    DeepSeek-V3

    Released Dec 26, 2024

    50/100
    • ECI132.3
    • Price$0.32 / $1.10
    • Context131K
    Full specs Remove DeepSeek-V3
  3. Our pick

    OpenAI

    GPT-4.1 mini

    Released Apr 14, 2025

    60/100
    • ECI135.0
    • Price$0.40 / $1.60
    • Context1.05M
    Full specs Remove GPT-4.1 mini
01 — Verdict

GPT-4.1 mini is our pick

GPT-4.1 mini is the better all-round choice, scoring 60/100 against QwQ 32B (53) and DeepSeek-V3 (50). It leads on inputs & features and context window. QwQ 32B wins on capability. DeepSeek-V3 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwQ 32BCapabilities Index (ECI): QwQ 32B 137.6 · GPT-4.1 mini 135.0 · DeepSeek-V3 132.3
  • Lowest priceDeepSeek-V3DeepSeek-V3 $0.515 · GPT-4.1 mini $0.70 · QwQ 32B $0.745 per 1M tokens (3:1 blend)
  • Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · QwQ 32B 131,072 · DeepSeek-V3 131,072 tokens
  • Widest inputsGPT-4.1 miniQwQ 32B: Text · DeepSeek-V3: Text · GPT-4.1 mini: Text, Images, PDFs
  • Self-hostingQwQ 32B and DeepSeek-V3Publishes downloadable weights (DeepSeek Model License)
How the score is built
MeasureWeightQwQ 32BDeepSeek-V3GPT-4.1 mini
CapabilityCapabilities Index (ECI)50%625659
Price25%566457
Inputs & features15%352570
Context window10%242461
Overall100%53/10050/10060/100
02 — Side by side

Every spec in one table

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

QwQ 32B vs DeepSeek-V3 vs GPT-4.1 mini specifications side by side
SpecificationQwQ 32BAlibaba (Qwen)DeepSeek-V3DeepSeekGPT-4.1 miniOpenAI
Capability
Capabilities Index (ECI)137.6 (best)132.3135.0
ECI rank#109 of 148 (best)#121 of 148#115 of 148
GPQA DiamondGraduate-level science questions65.3%56.5%65.9% (best)
FrontierMath Tiers 1–3Research-level mathematics——6.7%
OTIS Mock AIME 2024–2025Competition mathematics59.2% (best)15.8%44.7%
SimpleQA VerifiedShort factual questions——12.7%
Price per million tokens
Input$0.66$0.32 (best)$0.40
Output$1.00 (best)$1.10$1.60
Cached input——$0.10
Blended (3:1)$0.745$0.515 (best)$0.70
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 5 providersOfficial OpenAI API
Limits
Context window131,072 tokens131,072 tokens1,047,576 tokens (best)
Max output8,192 tokens8,192 tokens32,768 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenDeepSeek Model LicenseProprietary
API model ID——gpt-4.1-mini
API providers1524 (best)
ReleasedMar 5, 2025Dec 26, 2024Apr 14, 2025
Knowledge cutoffApr 2024—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.

  • QwQ 32B$8.60
  • DeepSeek-V3$5.40
  • GPT-4.1 mini$7.20
04 — Questions

Which should you choose?

Which is better: QwQ 32B, DeepSeek-V3 or GPT-4.1 mini?

GPT-4.1 mini is the better all-round choice, scoring 60/100 against QwQ 32B (53) and DeepSeek-V3 (50). It leads on inputs & features and context window. QwQ 32B wins on capability. DeepSeek-V3 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, QwQ 32B, DeepSeek-V3 or GPT-4.1 mini?

DeepSeek-V3 is cheaper at $0.32 input / $1.10 output per million tokens (median across 5 API providers). GPT-4.1 mini costs $0.40 input / $1.60 output per million tokens (official OpenAI API price); 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 $0.515 per million tokens for DeepSeek-V3 versus $0.70 for GPT-4.1 mini (1.4× as much) and $0.745 for QwQ 32B (1.4× as much).

Which scores higher on benchmarks?

QwQ 32B scores higher on the Capabilities Index (ECI): QwQ 32B 137.6 (#109 of 148), GPT-4.1 mini 135.0 (#115 of 148) and DeepSeek-V3 132.3 (#121 of 148). The confidence ranges of the top two overlap (133.1–141.7 vs 131.2–136.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-4.1 mini 65.9%, QwQ 32B 65.3%, DeepSeek-V3 56.5%; OTIS Mock AIME 2024–2025 — QwQ 32B 59.2%, GPT-4.1 mini 44.7%, DeepSeek-V3 15.8%.

Which is better for coding?

There are no published SWE-bench Verified results for QwQ 32B, DeepSeek-V3 and GPT-4.1 mini yet, so there is no like-for-like coding score. On overall capability, QwQ 32B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

GPT-4.1 mini has the largest context window at 1,047,576 tokens, against 131,072 for QwQ 32B and 131,072 for DeepSeek-V3. Maximum output per response: QwQ 32B up to 8,192, DeepSeek-V3 up to 8,192, GPT-4.1 mini up to 32,768 tokens.

Which can read images, PDFs, audio or video?

QwQ 32B accepts text; DeepSeek-V3 accepts text; GPT-4.1 mini accepts text, images and PDFs. GPT-4.1 mini handles the widest range of inputs.

Are any of these open source?

QwQ 32B and DeepSeek-V3 publishes its weights (DeepSeek Model License) and can be self-hosted; GPT-4.1 mini is proprietary.

Which is newer?

GPT-4.1 mini is the newest, released Apr 14, 2025. QwQ 32B came out Mar 5, 2025; DeepSeek-V3 came out Dec 26, 2024. Knowledge cutoff: QwQ 32B Apr 2024, GPT-4.1 mini 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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