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Comparison · 3 models · Updated Nov 2, 2026

Qwen3 235B-A22B Thinking 2507 vs Qwen MT Plus vs GLM-4.7

Too close to call on our weighted score (Qwen3 235B-A22B Thinking 2507 42, GLM-4.7 41, Qwen MT Plus 11). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen3 235B-A22B Thinking 2507

    Released Jul 25, 2025

    42/100
    • ECI143.8
    • Price$0.30 / $2.90
    • Context262K
    Full specs Remove Qwen3 235B-A22B Thinking 2507

  2. Alibaba (Qwen)

    Qwen MT Plus

    Released Jul 24, 2025

    11/100
    • ECI—
    • Price$2.46 / $7.37
    • Context16K
    Full specs Remove Qwen MT Plus

  3. 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
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Qwen3 235B-A22B Thinking 2507 42/100, GLM-4.7 41/100, Qwen MT Plus 11/100), so choose by what matters most for your work: Qwen3 235B-A22B Thinking 2507 on price and Qwen3 235B-A22B Thinking 2507 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 priceQwen3 235B-A22B Thinking 2507Qwen3 235B-A22B Thinking 2507 $0.95 · GLM-4.7 $1.00 · Qwen MT Plus $3.69 per 1M tokens (3:1 blend)
  • Longest contextQwen3 235B-A22B Thinking 2507Qwen3 235B-A22B Thinking 2507 262,144 · GLM-4.7 204,800 · Qwen MT Plus 16,384 tokens
  • Widest inputsSame inputsQwen3 235B-A22B Thinking 2507: Text · Qwen MT Plus: Text · GLM-4.7: Text
  • Self-hostingQwen3 235B-A22B Thinking 2507 and GLM-4.7Publishes downloadable weights (Apache 2.0)
How the score is built
MeasureWeightQwen3 235B-A22B Thinking 2507Qwen MT PlusGLM-4.7
Price50%492248
Inputs & features30%35035
Context window20%37032
Overall100%42/10011/10041/100

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 235B-A22B Thinking 2507 vs Qwen MT Plus vs GLM-4.7 specifications side by side
SpecificationQwen3 235B-A22B Thinking 2507Alibaba (Qwen)Qwen MT PlusAlibaba (Qwen)GLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)143.8 (best)—143.7
ECI rank#93 of 165 (best)—#94 of 165
GPQA DiamondGraduate-level science questions80.1%—83.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics86.7% (best)—83.3%
SimpleQA VerifiedShort factual questions40.4% (best)—32.2%
Price per million tokens
Input$0.30 (best)$2.46$0.60
Output$2.90$7.37$2.20 (best)
Cached input——$0.11
Blended (3:1)$0.95 (best)$3.69$1.00
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 11 providersOfficial Alibaba APIOfficial Z.AI API
Limits
Context window262,144 tokens (best)16,384 tokens204,800 tokens
Max output81,920 tokens8,192 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoYes
Tool callingYesNoYes
Structured outputNoNoNo
Availability
WeightsOpenApache 2.0ProprietaryOpen
API model ID—qwen-mt-plusglm-4.7
API providers12331 (best)
ReleasedJul 25, 2025Jul 24, 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 235B-A22B Thinking 2507$8.80
  • Qwen MT Plus$39.34
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

Which is better: Qwen3 235B-A22B Thinking 2507, Qwen MT Plus or GLM-4.7?

It is close. Our weighted score puts them within 1 points (Qwen3 235B-A22B Thinking 2507 42/100, GLM-4.7 41/100, Qwen MT Plus 11/100), so choose by what matters most for your work: Qwen3 235B-A22B Thinking 2507 on price and Qwen3 235B-A22B Thinking 2507 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 235B-A22B Thinking 2507, Qwen MT Plus or GLM-4.7?

Qwen3 235B-A22B Thinking 2507 is cheaper at $0.30 input / $2.90 output per million tokens (median across 11 API providers). GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price); Qwen MT Plus costs $2.46 input / $7.37 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.95 per million tokens for Qwen3 235B-A22B Thinking 2507 versus $1.00 for GLM-4.7 (1.1× as much) and $3.69 for Qwen MT Plus (3.9× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Qwen3 235B-A22B Thinking 2507 has an ECI of 143.8, Qwen MT Plus 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 235B-A22B Thinking 2507, Qwen MT Plus and GLM-4.7 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen MT Plus does not support tool calling, which most coding agents need.

Which has the bigger context window?

Qwen3 235B-A22B Thinking 2507 has the largest context window at 262,144 tokens, against 204,800 for GLM-4.7 and 16,384 for Qwen MT Plus. Maximum output per response: Qwen3 235B-A22B Thinking 2507 up to 81,920, Qwen MT Plus up to 8,192, GLM-4.7 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Qwen3 235B-A22B Thinking 2507 accepts text; Qwen MT Plus accepts text; GLM-4.7 accepts text. They handle the same number of input types.

Are any of these open source?

Qwen3 235B-A22B Thinking 2507 and GLM-4.7 publishes its weights (Apache 2.0) and can be self-hosted; Qwen MT Plus is proprietary.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. Qwen3 235B-A22B Thinking 2507 came out Jul 25, 2025; Qwen MT Plus came out Jul 24, 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

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