ZMIME
Comparison · 3 models · Updated Nov 2, 2026

GLM-4.7 vs Qwen3 235B-A22B Thinking 2507 vs Qwen3 30B-A3B Instruct 2507

Qwen3 30B-A3B Instruct 2507 comes out ahead, 59 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. 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
  3. Our pick

    Alibaba (Qwen)

    Qwen3 30B-A3B Instruct 2507

    Released Jul 28, 2025

    59/100
    • ECI137.3
    • Price$0.10 / $0.30
    • Context262K
    Full specs Remove Qwen3 30B-A3B Instruct 2507
01 — Verdict

Qwen3 30B-A3B Instruct 2507 is our pick

Qwen3 30B-A3B Instruct 2507 is the better all-round choice, scoring 59/100 against Qwen3 235B-A22B Thinking 2507 (55) and GLM-4.7 (55). It leads on price. 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 · Qwen3 30B-A3B Instruct 2507 137.3
  • Lowest priceQwen3 30B-A3B Instruct 2507Qwen3 30B-A3B Instruct 2507 $0.15 · 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 Qwen3 30B-A3B Instruct 2507Qwen3 235B-A22B Thinking 2507 262,144 · Qwen3 30B-A3B Instruct 2507 262,144 · GLM-4.7 204,800 tokens
  • Widest inputsSame inputsGLM-4.7: Text · Qwen3 235B-A22B Thinking 2507: Text · Qwen3 30B-A3B Instruct 2507: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGLM-4.7Qwen3 235B-A22B Thinking 2507Qwen3 30B-A3B Instruct 2507
CapabilityCapabilities Index (ECI)50%696961
Price25%484985
Inputs & features15%353525
Context window10%323737
Overall100%55/10055/10059/100
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 Qwen3 235B-A22B Thinking 2507 vs Qwen3 30B-A3B Instruct 2507 specifications side by side
SpecificationGLM-4.7Z.ai (Zhipu)Qwen3 235B-A22B Thinking 2507Alibaba (Qwen)Qwen3 30B-A3B Instruct 2507Alibaba (Qwen)
Capability
Capabilities Index (ECI)143.7143.8 (best)137.3
ECI rank#94 of 165#93 of 165 (best)#124 of 165
GPQA DiamondGraduate-level science questions83.3% (best)80.1%55.6%
OTIS Mock AIME 2024–2025Competition mathematics83.3%86.7% (best)62.2%
SimpleQA VerifiedShort factual questions32.2%40.4% (best)—
Price per million tokens
Input$0.60$0.30$0.10 (best)
Output$2.20$2.90$0.30 (best)
Cached input$0.11——
Blended (3:1)$1.00$0.95$0.15 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIMedian of 11 providersMedian of 12 providers
Limits
Context window204,800 tokens262,144 tokens (best)262,144 tokens (best)
Max output131,072 tokens (best)81,920 tokens16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenApache 2.0OpenApache 2.0
API model IDglm-4.7——
API providers31 (best)1214
ReleasedDec 22, 2025Jul 25, 2025Jul 28, 2025
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
  • Qwen3 235B-A22B Thinking 2507$8.80
  • Qwen3 30B-A3B Instruct 2507$1.60
04 — Questions

Which should you choose?

Which is better: GLM-4.7, Qwen3 235B-A22B Thinking 2507 or Qwen3 30B-A3B Instruct 2507?

Qwen3 30B-A3B Instruct 2507 is the better all-round choice, scoring 59/100 against Qwen3 235B-A22B Thinking 2507 (55) and GLM-4.7 (55). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GLM-4.7, Qwen3 235B-A22B Thinking 2507 or Qwen3 30B-A3B Instruct 2507?

Qwen3 30B-A3B Instruct 2507 is cheaper at $0.10 input / $0.30 output per million tokens (median across 12 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 $0.15 per million tokens for Qwen3 30B-A3B Instruct 2507 versus $0.95 for Qwen3 235B-A22B Thinking 2507 (6.3× as much) and $1.00 for GLM-4.7 (6.7× 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 Qwen3 30B-A3B Instruct 2507 137.3 (#124 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%, Qwen3 30B-A3B Instruct 2507 55.6%; OTIS Mock AIME 2024–2025 — Qwen3 235B-A22B Thinking 2507 86.7%, GLM-4.7 83.3%, Qwen3 30B-A3B Instruct 2507 62.2%.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.7, Qwen3 235B-A22B Thinking 2507 and Qwen3 30B-A3B Instruct 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?

Qwen3 235B-A22B Thinking 2507 and Qwen3 30B-A3B Instruct 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, Qwen3 235B-A22B Thinking 2507 up to 81,920, Qwen3 30B-A3B Instruct 2507 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7 accepts text; Qwen3 235B-A22B Thinking 2507 accepts text; Qwen3 30B-A3B Instruct 2507 accepts text. They handle the same number of input types.

Are any of these open source?

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

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. Qwen3 30B-A3B Instruct 2507 came out Jul 28, 2025; Qwen3 235B-A22B Thinking 2507 came out Jul 25, 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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