ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen3-Coder 30B-A3B Instruct vs QwQ 32B vs GLM-4.5V

GLM-4.5V comes out ahead, 49 to 43 and 41 on our weighted score, though QwQ 32B is 17% cheaper per token.

  1. Alibaba (Qwen)

    Qwen3-Coder 30B-A3B Instruct

    Released Apr 2025

    41/100
    • ECI—
    • Price$0.45 / $2.25
    • Context262K
    Full specs Remove Qwen3-Coder 30B-A3B Instruct

  2. Alibaba (Qwen)

    QwQ 32B

    Released Mar 5, 2025

    43/100
    • ECI137.6
    • Price$0.66 / $1.00
    • Context131K
    Full specs Remove QwQ 32B
  3. Our pick

    Z.ai (Zhipu)

    GLM-4.5V

    Released Aug 11, 2025

    49/100
    • ECI—
    • Price$0.60 / $1.80
    • Context64K
    Full specs Remove GLM-4.5V
01 — Verdict

GLM-4.5V is our pick

GLM-4.5V is the better all-round choice, scoring 49/100 against QwQ 32B (43) and Qwen3-Coder 30B-A3B Instruct (41). It leads on inputs & features. Qwen3-Coder 30B-A3B Instruct wins on context window. QwQ 32B wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceQwQ 32BQwQ 32B $0.745 · Qwen3-Coder 30B-A3B Instruct $0.90 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
  • Longest contextQwen3-Coder 30B-A3B InstructQwen3-Coder 30B-A3B Instruct 262,144 · QwQ 32B 131,072 · GLM-4.5V 64,000 tokens
  • Widest inputsGLM-4.5VQwen3-Coder 30B-A3B Instruct: Text · QwQ 32B: Text · GLM-4.5V: Text, Images, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3-Coder 30B-A3B InstructQwQ 32BGLM-4.5V
Price50%525652
Inputs & features30%253570
Context window20%372412
Overall100%41/10043/10049/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Qwen3-Coder 30B-A3B Instruct vs QwQ 32B vs GLM-4.5V specifications side by side
SpecificationQwen3-Coder 30B-A3B InstructAlibaba (Qwen)QwQ 32BAlibaba (Qwen)GLM-4.5VZ.ai (Zhipu)
Capability
Capabilities Index (ECI)—137.6—
ECI rank—#109 of 148—
GPQA DiamondGraduate-level science questions—65.3%—
OTIS Mock AIME 2024–2025Competition mathematics—59.2%—
Price per million tokens
Input$0.45 (best)$0.66$0.60
Output$2.25$1.00 (best)$1.80
Cached input———
Blended (3:1)$0.90$0.745 (best)$0.90
Long-context rateOver 32K: $0.75 / $3.75Same rateSame rate
Price sourceOfficial Alibaba APIMedian of 1 providersOfficial Z.AI API
Limits
Context window262,144 tokens (best)131,072 tokens64,000 tokens
Max output65,536 tokens (best)8,192 tokens16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoYes
ReasoningNoYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDqwen3-coder-30b-a3b-instruct—glm-4.5v
API providers13 (best)111
ReleasedApr 2025Mar 5, 2025Aug 11, 2025
Knowledge cutoffApr 2025Apr 2024Apr 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-Coder 30B-A3B Instruct$9.00
  • QwQ 32B$8.60
  • GLM-4.5V$9.60
04 — Questions

Which should you choose?

Which is better: Qwen3-Coder 30B-A3B Instruct, QwQ 32B or GLM-4.5V?

GLM-4.5V is the better all-round choice, scoring 49/100 against QwQ 32B (43) and Qwen3-Coder 30B-A3B Instruct (41). It leads on inputs & features. Qwen3-Coder 30B-A3B Instruct wins on context window. QwQ 32B wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Qwen3-Coder 30B-A3B Instruct, QwQ 32B or GLM-4.5V?

QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). Qwen3-Coder 30B-A3B Instruct costs $0.45 input / $2.25 output per million tokens (official Alibaba API price); GLM-4.5V costs $0.60 input / $1.80 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for QwQ 32B versus $0.90 for Qwen3-Coder 30B-A3B Instruct (1.2× as much) and $0.90 for GLM-4.5V (1.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Qwen3-Coder 30B-A3B Instruct has not been scored yet, QwQ 32B has an ECI of 137.6 and GLM-4.5V has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3-Coder 30B-A3B Instruct, QwQ 32B and GLM-4.5V yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen3-Coder 30B-A3B Instruct has the largest context window at 262,144 tokens, against 131,072 for QwQ 32B and 64,000 for GLM-4.5V. Maximum output per response: Qwen3-Coder 30B-A3B Instruct up to 65,536, QwQ 32B up to 8,192, GLM-4.5V up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen3-Coder 30B-A3B Instruct accepts text; QwQ 32B accepts text; GLM-4.5V accepts text, images and video. GLM-4.5V handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights, so you can self-host them.

Which is newer?

GLM-4.5V is the newest, released Aug 11, 2025. Qwen3-Coder 30B-A3B Instruct came out Apr 2025; QwQ 32B came out Mar 5, 2025. Knowledge cutoff: Qwen3-Coder 30B-A3B Instruct Apr 2025, QwQ 32B Apr 2024, GLM-4.5V 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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