ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GLM-4.7 vs MiniMax-M2.5-highspeed vs Qwen3.5 35B-A3B

Qwen3.5 35B-A3B comes out ahead, 63 to 42 and 41 on our weighted score, and it is the cheaper option too.

  1. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    42/100
    • ECI143.5
    • Price$0.60 / $2.20
    • Context205K
  2. MiniMax

    MiniMax-M2.5-highspeed

    Released Feb 13, 2026

    41/100
    • ECI—
    • Price$0.60 / $2.40
    • Context205K
  3. Our pick

    Alibaba (Qwen)

    Qwen3.5 35B-A3B

    Released Feb 23, 2026

    63/100
    • ECI142.5
    • Price$0.25 / $2.00
    • Context262K
01 — Verdict

Qwen3.5 35B-A3B is our pick

Qwen3.5 35B-A3B is the better all-round choice, scoring 63/100 against GLM-4.7 (42) and MiniMax-M2.5-highspeed (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 priceQwen3.5 35B-A3BQwen3.5 35B-A3B $0.688 · GLM-4.7 $1.00 · MiniMax-M2.5-highspeed $1.05 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 35B-A3BQwen3.5 35B-A3B 262,144 · GLM-4.7 204,800 · MiniMax-M2.5-highspeed 204,800 tokens
  • Widest inputsQwen3.5 35B-A3BGLM-4.7: Text · MiniMax-M2.5-highspeed: Text · Qwen3.5 35B-A3B: Text, Images, Audio, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGLM-4.7MiniMax-M2.5-highspeedQwen3.5 35B-A3B
Price50%504958
Inputs & features30%353590
Context window20%323237
Overall100%42/10041/10063/100

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.

GLM-4.7 vs MiniMax-M2.5-highspeed vs Qwen3.5 35B-A3B specifications side by side
SpecificationGLM-4.7Z.ai (Zhipu)MiniMax-M2.5-highspeedMiniMaxQwen3.5 35B-A3BAlibaba (Qwen)
Capability
Capabilities Index (ECI)143.5 (best)—142.5
ECI rank#84 of 148 (best)—#88 of 148
GPQA DiamondGraduate-level science questions83.3%—83.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics83.3% (best)—70.0%
SimpleQA VerifiedShort factual questions32.2%——
Price per million tokens
Input$0.60$0.60$0.25 (best)
Output$2.20$2.40$2.00 (best)
Cached input$0.11$0.06 (best)—
Blended (3:1)$1.00$1.05$0.688 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial MiniMax (minimax.io) APIOfficial Alibaba API
Limits
Context window204,800 tokens204,800 tokens262,144 tokens (best)
Max output131,072 tokens (best)131,072 tokens (best)65,536 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoYes
VideoNoNoYes
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenOpen
API model IDglm-4.7MiniMax-M2.5-highspeedqwen3.5-35b-a3b
API providers20 (best)718
ReleasedDec 22, 2025Feb 13, 2026Feb 23, 2026
Knowledge cutoffApr 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.

  • GLM-4.7$10.40
  • MiniMax-M2.5-highspeed$10.80
  • Qwen3.5 35B-A3B$6.50
04 — Questions

Which should you choose?

Which is better: GLM-4.7, MiniMax-M2.5-highspeed or Qwen3.5 35B-A3B?

Qwen3.5 35B-A3B is the better all-round choice, scoring 63/100 against GLM-4.7 (42) and MiniMax-M2.5-highspeed (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, GLM-4.7, MiniMax-M2.5-highspeed or Qwen3.5 35B-A3B?

Qwen3.5 35B-A3B is cheaper at $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); MiniMax-M2.5-highspeed costs $0.60 input / $2.40 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.688 per million tokens for Qwen3.5 35B-A3B versus $1.00 for GLM-4.7 (1.5× as much) and $1.05 for MiniMax-M2.5-highspeed (1.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. GLM-4.7 has an ECI of 143.5, MiniMax-M2.5-highspeed has not been scored yet and Qwen3.5 35B-A3B has an ECI of 142.5.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.7, MiniMax-M2.5-highspeed and Qwen3.5 35B-A3B 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?

Qwen3.5 35B-A3B has the largest context window at 262,144 tokens, against 204,800 for GLM-4.7 and 204,800 for MiniMax-M2.5-highspeed. Maximum output per response: GLM-4.7 up to 131,072, MiniMax-M2.5-highspeed up to 131,072, Qwen3.5 35B-A3B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7 accepts text; MiniMax-M2.5-highspeed accepts text; Qwen3.5 35B-A3B accepts text, images, audio and video. Qwen3.5 35B-A3B 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?

Qwen3.5 35B-A3B is the newest, released Feb 23, 2026. MiniMax-M2.5-highspeed came out Feb 13, 2026; GLM-4.7 came out Dec 22, 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 Oct 4, 2026.