ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Magistral Small vs QwQ 32B vs GPT-4.1 mini

GPT-4.1 mini comes out ahead, 60 to 53 and 50 on our weighted score, and it is the cheaper option too.

  1. Mistral AI

    Magistral Small

    Released Jun 10, 2025

    50/100
    • ECI133.2
    • Price$0.50 / $1.50
    • Context131K
    Full specs Remove Magistral Small

  2. Alibaba (Qwen)

    QwQ 32B

    Released Mar 5, 2025

    53/100
    • ECI137.6
    • Price$0.66 / $1.00
    • Context131K
    Full specs Remove QwQ 32B
  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 Magistral Small (50). It leads on inputs & features and context window. QwQ 32B wins on capability. 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 · Magistral Small 133.2
  • Lowest priceGPT-4.1 miniGPT-4.1 mini $0.70 · QwQ 32B $0.745 · Magistral Small $0.75 per 1M tokens (3:1 blend)
  • Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · Magistral Small 131,072 · QwQ 32B 131,072 tokens
  • Widest inputsGPT-4.1 miniMagistral Small: Text · QwQ 32B: Text · GPT-4.1 mini: Text, Images, PDFs
  • Self-hostingMagistral Small and QwQ 32BPublishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightMagistral SmallQwQ 32BGPT-4.1 mini
CapabilityCapabilities Index (ECI)50%576259
Price25%565657
Inputs & features15%353570
Context window10%242461
Overall100%50/10053/10060/100
02 — Side by side

Every spec in one table

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

Magistral Small vs QwQ 32B vs GPT-4.1 mini specifications side by side
SpecificationMagistral SmallMistral AIQwQ 32BAlibaba (Qwen)GPT-4.1 miniOpenAI
Capability
Capabilities Index (ECI)133.2137.6 (best)135.0
ECI rank#120 of 148#109 of 148 (best)#115 of 148
GPQA DiamondGraduate-level science questions56.1%65.3%65.9% (best)
FrontierMath Tiers 1–3Research-level mathematics——6.7%
OTIS Mock AIME 2024–2025Competition mathematics30.0%59.2% (best)44.7%
SimpleQA VerifiedShort factual questions——12.7%
Price per million tokens
Input$0.50$0.66$0.40 (best)
Output$1.50$1.00 (best)$1.60
Cached input——$0.10
Blended (3:1)$0.75$0.745$0.70 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 1 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
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenApache 2.0OpenProprietary
API model ID——gpt-4.1-mini
API providers1124 (best)
ReleasedJun 10, 2025Mar 5, 2025Apr 14, 2025
Knowledge cutoff—Apr 2024Apr 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.

  • Magistral Small$8.00
  • QwQ 32B$8.60
  • GPT-4.1 mini$7.20
04 — Questions

Which should you choose?

Which is better: Magistral Small, QwQ 32B or GPT-4.1 mini?

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

Which is cheaper, Magistral Small, QwQ 32B or GPT-4.1 mini?

GPT-4.1 mini is cheaper at $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); Magistral Small costs $0.50 input / $1.50 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for GPT-4.1 mini versus $0.745 for QwQ 32B (1.1× as much) and $0.75 for Magistral Small (1.1× 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 Magistral Small 133.2 (#120 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%, Magistral Small 56.1%; OTIS Mock AIME 2024–2025 — QwQ 32B 59.2%, GPT-4.1 mini 44.7%, Magistral Small 30.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Magistral Small, QwQ 32B 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 Magistral Small and 131,072 for QwQ 32B. Maximum output per response: Magistral Small up to 8,192, QwQ 32B up to 8,192, GPT-4.1 mini up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Magistral Small accepts text; QwQ 32B 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?

Magistral Small and QwQ 32B publishes its weights (Apache 2.0) and can be self-hosted; GPT-4.1 mini is proprietary.

Which is newer?

Magistral Small is the newest, released Jun 10, 2025. GPT-4.1 mini came out Apr 14, 2025; QwQ 32B came out Mar 5, 2025. 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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