ZMIME
Comparison · 3 models · Updated Nov 2, 2026

GLM-4.7 vs Gemma 4 31B IT vs Qwen3 235B-A22B Thinking 2507

Gemma 4 31B IT comes out ahead, 68 to 55 and 55 on our weighted score, and it is the cheaper option too.

  1. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    55/100
    • ECI143.7
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7
  2. Our pick

    Google

    Gemma 4 31B IT

    Released Apr 2, 2026

    68/100
    • ECI143.1
    • Price$0.14 / $0.40
    • Context262K
    Full specs Remove Gemma 4 31B IT

  3. Alibaba (Qwen)

    Qwen3 235B-A22B Thinking 2507

    Released Jul 25, 2025

    55/100
    • ECI143.8
    • Price$0.30 / $2.90
    • Context262K
    Full specs Remove Qwen3 235B-A22B Thinking 2507
01 — Verdict

Gemma 4 31B IT is our pick

Gemma 4 31B IT is the better all-round choice, scoring 68/100 against Qwen3 235B-A22B Thinking 2507 (55) and GLM-4.7 (55). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3 235B-A22B Thinking 2507Capabilities Index (ECI): Qwen3 235B-A22B Thinking 2507 143.8 · GLM-4.7 143.7 · Gemma 4 31B IT 143.1
  • Lowest priceGemma 4 31B ITGemma 4 31B IT $0.205 · Qwen3 235B-A22B Thinking 2507 $0.95 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
  • Longest contextGemma 4 31B IT and Qwen3 235B-A22B Thinking 2507Gemma 4 31B IT 262,144 · Qwen3 235B-A22B Thinking 2507 262,144 · GLM-4.7 204,800 tokens
  • Widest inputsGemma 4 31B ITGLM-4.7: Text · Gemma 4 31B IT: Text, Images · Qwen3 235B-A22B Thinking 2507: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGLM-4.7Gemma 4 31B ITQwen3 235B-A22B Thinking 2507
CapabilityCapabilities Index (ECI)50%696869
Price25%487949
Inputs & features15%357035
Context window10%323737
Overall100%55/10068/10055/100
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 Gemma 4 31B IT vs Qwen3 235B-A22B Thinking 2507 specifications side by side
SpecificationGLM-4.7Z.ai (Zhipu)Gemma 4 31B ITGoogleQwen3 235B-A22B Thinking 2507Alibaba (Qwen)
Capability
Capabilities Index (ECI)143.7143.1143.8 (best)
ECI rank#94 of 165#96 of 165#93 of 165 (best)
GPQA DiamondGraduate-level science questions83.3% (best)75.8%80.1%
OTIS Mock AIME 2024–2025Competition mathematics83.3%73.3%86.7% (best)
SimpleQA VerifiedShort factual questions32.2%10.4%40.4% (best)
Price per million tokens
Input$0.60$0.14 (best)$0.30
Output$2.20$0.40 (best)$2.90
Cached input$0.11——
Blended (3:1)$1.00$0.205 (best)$0.95
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIMedian of 36 providersMedian of 11 providers
Limits
Context window204,800 tokens262,144 tokens (best)262,144 tokens (best)
Max output131,072 tokens (best)32,768 tokens81,920 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenOpenOpenApache 2.0
API model IDglm-4.7gemma-4-31b-it—
API providers3146 (best)12
ReleasedDec 22, 2025Apr 2, 2026Jul 25, 2025
Knowledge cutoffApr 2025Jan 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
  • Gemma 4 31B IT$2.20
  • Qwen3 235B-A22B Thinking 2507$8.80
04 — Questions

Which should you choose?

Which is better: GLM-4.7, Gemma 4 31B IT or Qwen3 235B-A22B Thinking 2507?

Gemma 4 31B IT is the better all-round choice, scoring 68/100 against Qwen3 235B-A22B Thinking 2507 (55) and GLM-4.7 (55). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GLM-4.7, Gemma 4 31B IT or Qwen3 235B-A22B Thinking 2507?

Gemma 4 31B IT is cheaper at $0.14 input / $0.40 output per million tokens (median across 36 API providers). Qwen3 235B-A22B Thinking 2507 costs $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). At a typical mix of three input tokens to one output token, that is $0.205 per million tokens for Gemma 4 31B IT versus $0.95 for Qwen3 235B-A22B Thinking 2507 (4.6× as much) and $1.00 for GLM-4.7 (4.9× as much).

Which scores higher on benchmarks?

Qwen3 235B-A22B Thinking 2507 scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B Thinking 2507 143.8 (#93 of 165), GLM-4.7 143.7 (#94 of 165) and Gemma 4 31B IT 143.1 (#96 of 165). The confidence ranges of the top two overlap (141.9–145.2 vs 141.4–145.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-4.7 83.3%, Qwen3 235B-A22B Thinking 2507 80.1%, Gemma 4 31B IT 75.8%; OTIS Mock AIME 2024–2025 — Qwen3 235B-A22B Thinking 2507 86.7%, GLM-4.7 83.3%, Gemma 4 31B IT 73.3%; SimpleQA Verified — Qwen3 235B-A22B Thinking 2507 40.4%, GLM-4.7 32.2%, Gemma 4 31B IT 10.4%.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.7, Gemma 4 31B IT and Qwen3 235B-A22B Thinking 2507 yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B Thinking 2507 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Gemma 4 31B IT and Qwen3 235B-A22B Thinking 2507 have the largest context windows (262,144 and 262,144 tokens), against 204,800 for GLM-4.7. Maximum output per response: GLM-4.7 up to 131,072, Gemma 4 31B IT up to 32,768, Qwen3 235B-A22B Thinking 2507 up to 81,920 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7 accepts text; Gemma 4 31B IT accepts text and images; Qwen3 235B-A22B Thinking 2507 accepts text. Gemma 4 31B IT handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Gemma 4 31B IT is the newest, released Apr 2, 2026. GLM-4.7 came out Dec 22, 2025; Qwen3 235B-A22B Thinking 2507 came out Jul 25, 2025. Knowledge cutoff: GLM-4.7 Apr 2025, Gemma 4 31B IT Jan 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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