ZMIME
Comparison · 3 models · Updated Nov 2, 2026

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

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

  1. 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
  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. 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
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 contextQwen3 235B-A22B Thinking 2507 and Gemma 4 31B ITQwen3 235B-A22B Thinking 2507 262,144 · Gemma 4 31B IT 262,144 · GLM-4.7 204,800 tokens
  • Widest inputsGemma 4 31B ITQwen3 235B-A22B Thinking 2507: Text · Gemma 4 31B IT: Text, Images · GLM-4.7: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 235B-A22B Thinking 2507Gemma 4 31B ITGLM-4.7
CapabilityCapabilities Index (ECI)50%696869
Price25%497948
Inputs & features15%357035
Context window10%373732
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.

Qwen3 235B-A22B Thinking 2507 vs Gemma 4 31B IT vs GLM-4.7 specifications side by side
SpecificationQwen3 235B-A22B Thinking 2507Alibaba (Qwen)Gemma 4 31B ITGoogleGLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)143.8 (best)143.1143.7
ECI rank#93 of 165 (best)#96 of 165#94 of 165
GPQA DiamondGraduate-level science questions80.1%75.8%83.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics86.7% (best)73.3%83.3%
SimpleQA VerifiedShort factual questions40.4% (best)10.4%32.2%
Price per million tokens
Input$0.30$0.14 (best)$0.60
Output$2.90$0.40 (best)$2.20
Cached input——$0.11
Blended (3:1)$0.95$0.205 (best)$1.00
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 11 providersMedian of 36 providersOfficial Z.AI API
Limits
Context window262,144 tokens (best)262,144 tokens (best)204,800 tokens
Max output81,920 tokens32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsOpenApache 2.0OpenOpen
API model ID—gemma-4-31b-itglm-4.7
API providers1246 (best)31
ReleasedJul 25, 2025Apr 2, 2026Dec 22, 2025
Knowledge cutoff—Jan 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 235B-A22B Thinking 2507$8.80
  • Gemma 4 31B IT$2.20
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

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

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

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 Qwen3 235B-A22B Thinking 2507, Gemma 4 31B IT and GLM-4.7 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?

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

Which can read images, PDFs, audio or video?

Qwen3 235B-A22B Thinking 2507 accepts text; Gemma 4 31B IT accepts text and images; GLM-4.7 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: Gemma 4 31B IT Jan 2025, 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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