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Comparison · 2 models · Updated Oct 4, 2026

Qwen3 VL 235B A22B Thinking vs GLM-4.5V

Too close to call on our weighted score (GLM-4.5V 49, Qwen3 VL 235B A22B Thinking 48). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen3 VL 235B A22B Thinking

    Released Sep 23, 2025

    48/100
    • ECI—
    • Price$0.40 / $4.00
    • Context131K
    Full specs Remove Qwen3 VL 235B A22B Thinking

  2. 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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (GLM-4.5V 49/100, Qwen3 VL 235B A22B Thinking 48/100), so choose by what matters most for your work: GLM-4.5V on price and Qwen3 VL 235B A22B Thinking for long inputs. 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 priceGLM-4.5VGLM-4.5V $0.90 · Qwen3 VL 235B A22B Thinking $1.30 per 1M tokens (3:1 blend)
  • Longest contextQwen3 VL 235B A22B ThinkingQwen3 VL 235B A22B Thinking 131,072 · GLM-4.5V 64,000 tokens
  • Widest inputsGLM-4.5VQwen3 VL 235B A22B Thinking: Text, Images · 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 VL 235B A22B ThinkingGLM-4.5V
Price50%4452
Inputs & features30%7070
Context window20%2412
Overall100%48/10049/100

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 VL 235B A22B Thinking vs GLM-4.5V specifications side by side
SpecificationQwen3 VL 235B A22B ThinkingAlibaba (Qwen)GLM-4.5VZ.ai (Zhipu)
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.40 (best)$0.60
Output$4.00$1.80 (best)
Cached input——
Blended (3:1)$1.30$0.90 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 9 providersOfficial Z.AI API
Limits
Context window131,072 tokens (best)64,000 tokens
Max output32,768 tokens (best)16,384 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoYes
ReasoningYesYes
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenOpen
API model ID—glm-4.5v
API providers911 (best)
ReleasedSep 23, 2025Aug 11, 2025
Knowledge cutoffMar 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 VL 235B A22B Thinking$12.00
  • GLM-4.5V$9.60
04 — Questions

Which should you choose?

Which is better: Qwen3 VL 235B A22B Thinking or GLM-4.5V?

It is close. Our weighted score puts them within 1 points (GLM-4.5V 49/100, Qwen3 VL 235B A22B Thinking 48/100), so choose by what matters most for your work: GLM-4.5V on price and Qwen3 VL 235B A22B Thinking for long inputs. 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 235B A22B Thinking or GLM-4.5V?

GLM-4.5V is cheaper at $0.60 input / $1.80 output per million tokens (official Z.AI API price). Qwen3 VL 235B A22B Thinking costs $0.40 input / $4.00 output per million tokens (median across 9 API providers). At a typical mix of three input tokens to one output token, that is $0.90 per million tokens for GLM-4.5V versus $1.30 for Qwen3 VL 235B A22B Thinking (1.4× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen3 VL 235B A22B Thinking has not been scored yet and GLM-4.5V has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 VL 235B A22B Thinking and GLM-4.5V 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 235B A22B Thinking has the largest context window at 131,072 tokens, against 64,000 for GLM-4.5V. Maximum output per response: Qwen3 VL 235B A22B Thinking up to 32,768, GLM-4.5V up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen3 VL 235B A22B Thinking accepts text and images; GLM-4.5V accepts text, images and video. GLM-4.5V handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Qwen3 VL 235B A22B Thinking is the newest, released Sep 23, 2025. GLM-4.5V came out Aug 11, 2025. Knowledge cutoff: Qwen3 VL 235B A22B Thinking Mar 31, 2025, 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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