ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen3.5 9B vs GPT-5.4 nano vs GPT-5 Nano

Too close to call on our weighted score (Qwen3.5 9B 72, GPT-5 Nano 70, GPT-5.4 nano 68). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen3.5 9B

    Released Feb 23, 2026

    72/100
    • ECI139.5
    • Price$0.10 / $0.15
    • Context262K
    Full specs Remove Qwen3.5 9B

  2. OpenAI

    GPT-5.4 nano

    Released Mar 17, 2026

    68/100
    • ECI145.8
    • Price$0.20 / $1.25
    • Context400K
    Full specs Remove GPT-5.4 nano

  3. OpenAI

    GPT-5 Nano

    Released Aug 7, 2025

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

Too close to call

It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, GPT-5.4 nano 68/100), so choose by what matters most for your work: GPT-5.4 nano for raw capability and Qwen3.5 9B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5.4 nanoCapabilities Index (ECI): GPT-5.4 nano 145.8 · Qwen3.5 9B 139.5 · GPT-5 Nano 139.4
  • Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · GPT-5 Nano $0.138 · GPT-5.4 nano $0.463 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.4 nano and GPT-5 NanoGPT-5.4 nano 400,000 · GPT-5 Nano 400,000 · Qwen3.5 9B 262,144 tokens
  • Widest inputsQwen3.5 9BQwen3.5 9B: Text, Images, Video · GPT-5.4 nano: Text, Images · GPT-5 Nano: Text, Images
  • Self-hostingQwen3.5 9BPublishes downloadable weights
How the score is built
MeasureWeightQwen3.5 9BGPT-5.4 nanoGPT-5 Nano
CapabilityCapabilities Index (ECI)50%657365
Price25%956691
Inputs & features15%807070
Context window10%374444
Overall100%72/10068/10070/100
02 — Side by side

Every spec in one table

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

Qwen3.5 9B vs GPT-5.4 nano vs GPT-5 Nano specifications side by side
SpecificationQwen3.5 9BAlibaba (Qwen)GPT-5.4 nanoOpenAIGPT-5 NanoOpenAI
Capability
Capabilities Index (ECI)139.5145.8 (best)139.4
ECI rank#101 of 148#75 of 148 (best)#102 of 148
GPQA DiamondGraduate-level science questions79.0% (best)78.5%69.4%
FrontierMath Tiers 1–3Research-level mathematics—44.9% (best)20.0%
OTIS Mock AIME 2024–2025Competition mathematics61.7%87.8% (best)81.1%
SimpleQA VerifiedShort factual questions—11.7%11.7%
Price per million tokens
Input$0.10$0.20$0.05 (best)
Output$0.15 (best)$1.25$0.40
Cached input—$0.02$0.005 (best)
Blended (3:1)$0.113 (best)$0.463$0.138
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 14 providersOfficial OpenAI APIOfficial OpenAI API
Limits
Context window262,144 tokens400,000 tokens (best)400,000 tokens (best)
Max output65,536 tokens128,000 tokens (best)128,000 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoNo
AudioNoNoNo
VideoYesNoNo
ReasoningYesYeslow · medium · high · xhighYesminimal · low · medium · high
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsOpenProprietaryProprietary
API model ID—gpt-5.4-nanogpt-5-nano
API providers1526 (best)21
ReleasedFeb 23, 2026Mar 17, 2026Aug 7, 2025
Knowledge cutoff—Aug 31, 2025May 30, 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.

  • Qwen3.5 9B$1.30
  • GPT-5.4 nano$4.50
  • GPT-5 Nano$1.30
04 — Questions

Which should you choose?

Which is better: Qwen3.5 9B, GPT-5.4 nano or GPT-5 Nano?

It is close. Our weighted score puts them within 2 points (Qwen3.5 9B 72/100, GPT-5 Nano 70/100, GPT-5.4 nano 68/100), so choose by what matters most for your work: GPT-5.4 nano for raw capability and Qwen3.5 9B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3.5 9B, GPT-5.4 nano or GPT-5 Nano?

Qwen3.5 9B is cheaper at $0.10 input / $0.15 output per million tokens (median across 14 API providers). GPT-5 Nano costs $0.05 input / $0.40 output per million tokens (official OpenAI API price); GPT-5.4 nano costs $0.20 input / $1.25 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.113 per million tokens for Qwen3.5 9B versus $0.138 for GPT-5 Nano (1.2× as much) and $0.463 for GPT-5.4 nano (4.1× as much).

Which scores higher on benchmarks?

GPT-5.4 nano scores higher on the Capabilities Index (ECI): GPT-5.4 nano 145.8 (#75 of 148), Qwen3.5 9B 139.5 (#101 of 148) and GPT-5 Nano 139.4 (#102 of 148). Their confidence ranges do not overlap (143.2–147.7 vs 136.5–141.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, GPT-5.4 nano 78.5%, GPT-5 Nano 69.4%; OTIS Mock AIME 2024–2025 — GPT-5.4 nano 87.8%, GPT-5 Nano 81.1%, Qwen3.5 9B 61.7%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 9B, GPT-5.4 nano and GPT-5 Nano yet, so there is no like-for-like coding score. On overall capability, GPT-5.4 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-5.4 nano and GPT-5 Nano have the largest context windows (400,000 and 400,000 tokens), against 262,144 for Qwen3.5 9B. Maximum output per response: Qwen3.5 9B up to 65,536, GPT-5.4 nano up to 128,000, GPT-5 Nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Qwen3.5 9B accepts text, images and video; GPT-5.4 nano accepts text and images; GPT-5 Nano accepts text and images. Qwen3.5 9B handles the widest range of inputs.

Are any of these open source?

Qwen3.5 9B publishes its weights and can be self-hosted; GPT-5.4 nano and GPT-5 Nano is proprietary.

Which is newer?

GPT-5.4 nano is the newest, released Mar 17, 2026. Qwen3.5 9B came out Feb 23, 2026; GPT-5 Nano came out Aug 7, 2025. Knowledge cutoff: GPT-5.4 nano Aug 31, 2025, GPT-5 Nano May 30, 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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