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Comparison · 3 models · Updated Nov 2, 2026

Codestral 25.08 vs GLM-4.5-Air vs Qwen3-VL Plus

Qwen3-VL Plus comes out ahead, 58 to 48 and 47 on our weighted score, though GLM-4.5-Air is 23% cheaper per token.

  1. Mistral AI

    Codestral 25.08

    Released Jul 30, 2025

    47/100
    • ECI—
    • Price$0.30 / $0.90
    • Context128K
    Full specs Remove Codestral 25.08

  2. Z.ai (Zhipu)

    GLM-4.5-Air

    Released Jul 28, 2025

    48/100
    • ECI—
    • Price$0.20 / $1.10
    • Context131K
    Full specs Remove GLM-4.5-Air
  3. Our pick

    Alibaba (Qwen)

    Qwen3-VL Plus

    Released Sep 23, 2025

    58/100
    • ECI—
    • Price$0.20 / $1.60
    • Context262K
    Full specs Remove Qwen3-VL Plus
01 — Verdict

Qwen3-VL Plus is our pick

Qwen3-VL Plus is the better all-round choice, scoring 58/100 against GLM-4.5-Air (48) and Codestral 25.08 (47). It leads on 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 priceGLM-4.5-AirGLM-4.5-Air $0.425 · Codestral 25.08 $0.45 · Qwen3-VL Plus $0.55 per 1M tokens (3:1 blend)
  • Longest contextQwen3-VL PlusQwen3-VL Plus 262,144 · GLM-4.5-Air 131,072 · Codestral 25.08 128,000 tokens
  • Widest inputsQwen3-VL PlusCodestral 25.08: Text · GLM-4.5-Air: Text · Qwen3-VL Plus: Text, Images
  • Self-hostingGLM-4.5-AirPublishes downloadable weights
How the score is built
MeasureWeightCodestral 25.08GLM-4.5-AirQwen3-VL Plus
Price50%646560
Inputs & features30%353570
Context window20%242537
Overall100%47/10048/10058/100

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.

Codestral 25.08 vs GLM-4.5-Air vs Qwen3-VL Plus specifications side by side
SpecificationCodestral 25.08Mistral AIGLM-4.5-AirZ.ai (Zhipu)Qwen3-VL PlusAlibaba (Qwen)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.30$0.20 (best)$0.20 (best)
Output$0.90 (best)$1.10$1.60
Cached input$0.03 (best)$0.03 (best)$0.04
Blended (3:1)$0.45$0.425 (best)$0.55
Long-context rateSame rateSame rateOver 32K: $0.30 / $2.40
Price sourceOfficial Mistral APIOfficial Z.AI APIOfficial Alibaba API
Limits
Context window128,000 tokens131,072 tokens262,144 tokens (best)
Max output8,192 tokens98,304 tokens (best)32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesYes
Tool callingYesYesYes
Structured outputYesNoYes
Availability
WeightsProprietaryOpenProprietary
API model IDcodestral-2508glm-4.5-airqwen3-vl-plus
API providers1119 (best)6
ReleasedJul 30, 2025Jul 28, 2025Sep 23, 2025
Knowledge cutoff—Apr 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.

  • Codestral 25.08$4.80
  • GLM-4.5-Air$4.20
  • Qwen3-VL Plus$5.20
04 — Questions

Which should you choose?

Which is better: Codestral 25.08, GLM-4.5-Air or Qwen3-VL Plus?

Qwen3-VL Plus is the better all-round choice, scoring 58/100 against GLM-4.5-Air (48) and Codestral 25.08 (47). It leads on 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, Codestral 25.08, GLM-4.5-Air or Qwen3-VL Plus?

GLM-4.5-Air is cheaper at $0.20 input / $1.10 output per million tokens (official Z.AI API price). Codestral 25.08 costs $0.30 input / $0.90 output per million tokens (official Mistral API price); Qwen3-VL Plus costs $0.20 input / $1.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.425 per million tokens for GLM-4.5-Air versus $0.45 for Codestral 25.08 (1.1× as much) and $0.55 for Qwen3-VL Plus (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Codestral 25.08 has not been scored yet, GLM-4.5-Air has not been scored yet and Qwen3-VL Plus has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Codestral 25.08, GLM-4.5-Air and Qwen3-VL Plus 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-VL Plus has the largest context window at 262,144 tokens, against 131,072 for GLM-4.5-Air and 128,000 for Codestral 25.08. Maximum output per response: Codestral 25.08 up to 8,192, GLM-4.5-Air up to 98,304, Qwen3-VL Plus up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Codestral 25.08 accepts text; GLM-4.5-Air accepts text; Qwen3-VL Plus accepts text and images. Qwen3-VL Plus handles the widest range of inputs.

Are any of these open source?

GLM-4.5-Air publishes its weights and can be self-hosted; Codestral 25.08 and Qwen3-VL Plus is proprietary.

Which is newer?

Qwen3-VL Plus is the newest, released Sep 23, 2025. Codestral 25.08 came out Jul 30, 2025; GLM-4.5-Air came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Air Apr 2025, Qwen3-VL Plus 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

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