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Comparison · 3 models · Updated Oct 4, 2026

GPT-4.1 mini vs GPT-5 Nano vs QwQ 32B

GPT-5 Nano comes out ahead, 70 to 60 and 53 on our weighted score, and it is the cheaper option too.

  1. 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
  2. Our pick

    OpenAI

    GPT-5 Nano

    Released Aug 7, 2025

    70/100
    • ECI139.4
    • Price$0.05 / $0.40
    • Context400K
    Full specs Remove GPT-5 Nano

  3. Alibaba (Qwen)

    QwQ 32B

    Released Mar 5, 2025

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

GPT-5 Nano is our pick

GPT-5 Nano is the better all-round choice, scoring 70/100 against GPT-4.1 mini (60) and QwQ 32B (53). It leads on capability and price. GPT-4.1 mini wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5 NanoCapabilities Index (ECI): GPT-5 Nano 139.4 · QwQ 32B 137.6 · GPT-4.1 mini 135.0
  • Lowest priceGPT-5 NanoGPT-5 Nano $0.138 · 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 · GPT-5 Nano 400,000 · QwQ 32B 131,072 tokens
  • Widest inputsGPT-4.1 miniGPT-4.1 mini: Text, Images, PDFs · GPT-5 Nano: Text, Images · QwQ 32B: Text
  • Self-hostingQwQ 32BPublishes downloadable weights
How the score is built
MeasureWeightGPT-4.1 miniGPT-5 NanoQwQ 32B
CapabilityCapabilities Index (ECI)50%596562
Price25%579156
Inputs & features15%707035
Context window10%614424
Overall100%60/10070/10053/100
02 — Side by side

Every spec in one table

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

GPT-4.1 mini vs GPT-5 Nano vs QwQ 32B specifications side by side
SpecificationGPT-4.1 miniOpenAIGPT-5 NanoOpenAIQwQ 32BAlibaba (Qwen)
Capability
Capabilities Index (ECI)135.0139.4 (best)137.6
ECI rank#115 of 148#102 of 148 (best)#109 of 148
GPQA DiamondGraduate-level science questions65.9%69.4% (best)65.3%
FrontierMath Tiers 1–3Research-level mathematics6.7%20.0% (best)—
OTIS Mock AIME 2024–2025Competition mathematics44.7%81.1% (best)59.2%
SimpleQA VerifiedShort factual questions12.7% (best)11.7%—
Price per million tokens
Input$0.40$0.05 (best)$0.66
Output$1.60$0.40 (best)$1.00
Cached input$0.10$0.005 (best)—
Blended (3:1)$0.70$0.138 (best)$0.745
Long-context rateSame rateSame rateSame rate
Price sourceOfficial OpenAI APIOfficial OpenAI APIMedian of 1 providers
Limits
Context window1,047,576 tokens (best)400,000 tokens131,072 tokens
Max output32,768 tokens128,000 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesminimal · low · medium · highYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsProprietaryProprietaryOpen
API model IDgpt-4.1-minigpt-5-nano—
API providers24 (best)211
ReleasedApr 14, 2025Aug 7, 2025Mar 5, 2025
Knowledge cutoffApr 2024May 30, 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.

  • GPT-4.1 mini$7.20
  • GPT-5 Nano$1.30
  • QwQ 32B$8.60
04 — Questions

Which should you choose?

Which is better: GPT-4.1 mini, GPT-5 Nano or QwQ 32B?

GPT-5 Nano is the better all-round choice, scoring 70/100 against GPT-4.1 mini (60) and QwQ 32B (53). It leads on capability and price. GPT-4.1 mini wins on context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-4.1 mini, GPT-5 Nano or QwQ 32B?

GPT-5 Nano is cheaper at $0.05 input / $0.40 output per million tokens (official OpenAI API price). 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 $0.138 per million tokens for GPT-5 Nano versus $0.70 for GPT-4.1 mini (5.1× as much) and $0.745 for QwQ 32B (5.4× as much).

Which scores higher on benchmarks?

GPT-5 Nano scores higher on the Capabilities Index (ECI): GPT-5 Nano 139.4 (#102 of 148), QwQ 32B 137.6 (#109 of 148) and GPT-4.1 mini 135.0 (#115 of 148). The confidence ranges of the top two overlap (134.9–141.7 vs 133.1–141.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-5 Nano 69.4%, GPT-4.1 mini 65.9%, QwQ 32B 65.3%; OTIS Mock AIME 2024–2025 — GPT-5 Nano 81.1%, QwQ 32B 59.2%, GPT-4.1 mini 44.7%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-4.1 mini, GPT-5 Nano and QwQ 32B yet, so there is no like-for-like coding score. On overall capability, GPT-5 Nano 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 400,000 for GPT-5 Nano and 131,072 for QwQ 32B. Maximum output per response: GPT-4.1 mini up to 32,768, GPT-5 Nano up to 128,000, QwQ 32B up to 8,192 tokens.

Which can read images, PDFs, audio or video?

GPT-4.1 mini accepts text, images and PDFs; GPT-5 Nano accepts text and images; QwQ 32B accepts text. GPT-4.1 mini handles the widest range of inputs.

Are any of these open source?

QwQ 32B publishes its weights and can be self-hosted; GPT-4.1 mini and GPT-5 Nano is proprietary.

Which is newer?

GPT-5 Nano is the newest, released Aug 7, 2025. GPT-4.1 mini came out Apr 14, 2025; QwQ 32B came out Mar 5, 2025. Knowledge cutoff: GPT-4.1 mini Apr 2024, GPT-5 Nano May 30, 2024, 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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