ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Qwen3 VL 30B A3B Instruct vs GLM-4.7

Qwen3 VL 30B A3B Instruct comes out ahead, 62 to 41 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen3 VL 30B A3B Instruct

    Released Oct 4, 2025

    62/100
    • ECI—
    • Price$0.15 / $0.60
    • Context262K
    Full specs Remove Qwen3 VL 30B A3B Instruct

  2. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    41/100
    • ECI143.7
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3 VL 30B A3B Instruct is our pick

Qwen3 VL 30B A3B Instruct is the better all-round choice, scoring 62/100 against GLM-4.7 (41). It leads on price, inputs & features and context window. 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 priceQwen3 VL 30B A3B InstructQwen3 VL 30B A3B Instruct $0.263 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
  • Longest contextQwen3 VL 30B A3B InstructQwen3 VL 30B A3B Instruct 262,144 · GLM-4.7 204,800 tokens
  • Widest inputsQwen3 VL 30B A3B InstructQwen3 VL 30B A3B Instruct: Text, Images, Video · GLM-4.7: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 VL 30B A3B InstructGLM-4.7
Price50%7448
Inputs & features30%6035
Context window20%3732
Overall100%62/10041/100

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 VL 30B A3B Instruct vs GLM-4.7 specifications side by side
SpecificationQwen3 VL 30B A3B InstructAlibaba (Qwen)GLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)—143.7
ECI rank—#94 of 165
GPQA DiamondGraduate-level science questions—83.3%
OTIS Mock AIME 2024–2025Competition mathematics—83.3%
SimpleQA VerifiedShort factual questions—32.2%
Price per million tokens
Input$0.15 (best)$0.60
Output$0.60 (best)$2.20
Cached input—$0.11
Blended (3:1)$0.263 (best)$1.00
Long-context rateSame rateSame rate
Price sourceMedian of 13 providersOfficial Z.AI API
Limits
Context window262,144 tokens (best)204,800 tokens
Max output32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoYesNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenApache-2.0Open
API model ID—glm-4.7
API providers1331 (best)
ReleasedOct 4, 2025Dec 22, 2025
Knowledge cutoff—Apr 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 VL 30B A3B Instruct$2.70
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

Which is better: Qwen3 VL 30B A3B Instruct or GLM-4.7?

Qwen3 VL 30B A3B Instruct is the better all-round choice, scoring 62/100 against GLM-4.7 (41). It leads on price, inputs & features and context window. 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 VL 30B A3B Instruct or GLM-4.7?

Qwen3 VL 30B A3B Instruct is cheaper at $0.15 input / $0.60 output per million tokens (median across 13 API providers). 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 $0.263 per million tokens for Qwen3 VL 30B A3B Instruct versus $1.00 for GLM-4.7 (3.8× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen3 VL 30B A3B Instruct has not been scored yet and GLM-4.7 has an ECI of 143.7.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 VL 30B A3B Instruct and GLM-4.7 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Qwen3 VL 30B A3B Instruct has the largest context window at 262,144 tokens, against 204,800 for GLM-4.7. Maximum output per response: Qwen3 VL 30B A3B Instruct up to 32,768, GLM-4.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Qwen3 VL 30B A3B Instruct accepts text, images and video; GLM-4.7 accepts text. Qwen3 VL 30B A3B Instruct handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights (Apache-2.0), so you can self-host them.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. Qwen3 VL 30B A3B Instruct came out Oct 4, 2025. Knowledge cutoff: 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 Nov 2, 2026.

05 — Keep comparing

Related comparisons