ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen3.5 35B-A3B vs GPT-5.4 nano vs GLM-4.7

Too close to call on our weighted score (GPT-5.4 nano 68, Qwen3.5 35B-A3B 66, GLM-4.7 56). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen3.5 35B-A3B

    Released Feb 23, 2026

    66/100
    • ECI142.5
    • Price$0.25 / $2.00
    • Context262K
    Full specs Remove Qwen3.5 35B-A3B

  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. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    56/100
    • ECI143.5
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (GPT-5.4 nano 68/100, Qwen3.5 35B-A3B 66/100, GLM-4.7 56/100), so choose by what matters most for your work: GPT-5.4 nano for raw capability. 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 · GLM-4.7 143.5 · Qwen3.5 35B-A3B 142.5
  • Lowest priceGPT-5.4 nanoGPT-5.4 nano $0.463 · Qwen3.5 35B-A3B $0.688 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.4 nanoGPT-5.4 nano 400,000 · Qwen3.5 35B-A3B 262,144 · GLM-4.7 204,800 tokens
  • Widest inputsQwen3.5 35B-A3BQwen3.5 35B-A3B: Text, Images, Audio, Video · GPT-5.4 nano: Text, Images · GLM-4.7: Text
  • Self-hostingQwen3.5 35B-A3B and GLM-4.7Publishes downloadable weights
How the score is built
MeasureWeightQwen3.5 35B-A3BGPT-5.4 nanoGLM-4.7
CapabilityCapabilities Index (ECI)50%697370
Price25%586650
Inputs & features15%907035
Context window10%374432
Overall100%66/10068/10056/100
02 — Side by side

Every spec in one table

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

Qwen3.5 35B-A3B vs GPT-5.4 nano vs GLM-4.7 specifications side by side
SpecificationQwen3.5 35B-A3BAlibaba (Qwen)GPT-5.4 nanoOpenAIGLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)142.5145.8 (best)143.5
ECI rank#88 of 148#75 of 148 (best)#84 of 148
GPQA DiamondGraduate-level science questions83.5% (best)78.5%83.3%
FrontierMath Tiers 1–3Research-level mathematics—44.9%—
OTIS Mock AIME 2024–2025Competition mathematics70.0%87.8% (best)83.3%
SimpleQA VerifiedShort factual questions—11.7%32.2% (best)
Price per million tokens
Input$0.25$0.20 (best)$0.60
Output$2.00$1.25 (best)$2.20
Cached input—$0.02 (best)$0.11
Blended (3:1)$0.688$0.463 (best)$1.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial OpenAI APIOfficial Z.AI API
Limits
Context window262,144 tokens400,000 tokens (best)204,800 tokens
Max output65,536 tokens128,000 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsNoNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesYeslow · medium · high · xhighYes
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsOpenProprietaryOpen
API model IDqwen3.5-35b-a3bgpt-5.4-nanoglm-4.7
API providers1826 (best)20
ReleasedFeb 23, 2026Mar 17, 2026Dec 22, 2025
Knowledge cutoff—Aug 31, 2025Apr 2025
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 35B-A3B$6.50
  • GPT-5.4 nano$4.50
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

Which is better: Qwen3.5 35B-A3B, GPT-5.4 nano or GLM-4.7?

It is close. Our weighted score puts them within 2 points (GPT-5.4 nano 68/100, Qwen3.5 35B-A3B 66/100, GLM-4.7 56/100), so choose by what matters most for your work: GPT-5.4 nano for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3.5 35B-A3B, GPT-5.4 nano or GLM-4.7?

GPT-5.4 nano is cheaper at $0.20 input / $1.25 output per million tokens (official OpenAI API price). Qwen3.5 35B-A3B costs $0.25 input / $2.00 output per million tokens (official Alibaba API price); GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.463 per million tokens for GPT-5.4 nano versus $0.688 for Qwen3.5 35B-A3B (1.5× as much) and $1.00 for GLM-4.7 (2.2× 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), GLM-4.7 143.5 (#84 of 148) and Qwen3.5 35B-A3B 142.5 (#88 of 148). The confidence ranges of the top two overlap (143.2–147.7 vs 141.3–145.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3.5 35B-A3B 83.5%, GLM-4.7 83.3%, GPT-5.4 nano 78.5%; OTIS Mock AIME 2024–2025 — GPT-5.4 nano 87.8%, GLM-4.7 83.3%, Qwen3.5 35B-A3B 70.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3.5 35B-A3B, GPT-5.4 nano and GLM-4.7 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 has the largest context window at 400,000 tokens, against 262,144 for Qwen3.5 35B-A3B and 204,800 for GLM-4.7. Maximum output per response: Qwen3.5 35B-A3B up to 65,536, GPT-5.4 nano up to 128,000, GLM-4.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Qwen3.5 35B-A3B accepts text, images, audio and video; GPT-5.4 nano accepts text and images; GLM-4.7 accepts text. Qwen3.5 35B-A3B handles the widest range of inputs.

Are any of these open source?

Qwen3.5 35B-A3B and GLM-4.7 publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.

Which is newer?

GPT-5.4 nano is the newest, released Mar 17, 2026. Qwen3.5 35B-A3B came out Feb 23, 2026; GLM-4.7 came out Dec 22, 2025. Knowledge cutoff: GPT-5.4 nano Aug 31, 2025, GLM-4.7 Apr 2025.

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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