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Comparison · 3 models · Updated Nov 2, 2026

Qwen3 235B-A22B Thinking 2507 vs DeepSeek R1 0528 vs GLM-4.7

Too close to call on our weighted score (Qwen3 235B-A22B Thinking 2507 55, GLM-4.7 55, DeepSeek R1 0528 53). The right pick depends on what you value most.

  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. DeepSeek

    DeepSeek R1 0528

    Released May 28, 2025

    53/100
    • ECI141.2
    • Price$0.512 / $2.19
    • Context164K
    Full specs Remove DeepSeek R1 0528

  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

Too close to call

It is close. Our weighted score puts them within a point (Qwen3 235B-A22B Thinking 2507 55/100, GLM-4.7 55/100, DeepSeek R1 0528 53/100), so choose by what matters most for your work: Qwen3 235B-A22B Thinking 2507 for raw capability and DeepSeek R1 0528 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 · DeepSeek R1 0528 141.2
  • Lowest priceDeepSeek R1 0528DeepSeek R1 0528 $0.932 · Qwen3 235B-A22B Thinking 2507 $0.95 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
  • Longest contextQwen3 235B-A22B Thinking 2507Qwen3 235B-A22B Thinking 2507 262,144 · GLM-4.7 204,800 · DeepSeek R1 0528 163,840 tokens
  • Widest inputsSame inputsQwen3 235B-A22B Thinking 2507: Text · DeepSeek R1 0528: Text · 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 2507DeepSeek R1 0528GLM-4.7
CapabilityCapabilities Index (ECI)50%696669
Price25%494948
Inputs & features15%353535
Context window10%372832
Overall100%55/10053/10055/100
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 DeepSeek R1 0528 vs GLM-4.7 specifications side by side
SpecificationQwen3 235B-A22B Thinking 2507Alibaba (Qwen)DeepSeek R1 0528DeepSeekGLM-4.7Z.ai (Zhipu)
Capability
Capabilities Index (ECI)143.8 (best)141.2143.7
ECI rank#93 of 165 (best)#108 of 165#94 of 165
GPQA DiamondGraduate-level science questions80.1%76.3%83.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics86.7% (best)66.4%83.3%
SimpleQA VerifiedShort factual questions40.4% (best)—32.2%
Price per million tokens
Input$0.30 (best)$0.512$0.60
Output$2.90$2.19 (best)$2.20
Cached input——$0.11
Blended (3:1)$0.95$0.932 (best)$1.00
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 11 providersMedian of 16 providersOfficial Z.AI API
Limits
Context window262,144 tokens (best)163,840 tokens204,800 tokens
Max output81,920 tokens32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenApache 2.0OpenMITOpen
API model ID——glm-4.7
API providers121631 (best)
ReleasedJul 25, 2025May 28, 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
  • DeepSeek R1 0528$9.50
  • GLM-4.7$10.40
04 — Questions

Which should you choose?

Which is better: Qwen3 235B-A22B Thinking 2507, DeepSeek R1 0528 or GLM-4.7?

It is close. Our weighted score puts them within a point (Qwen3 235B-A22B Thinking 2507 55/100, GLM-4.7 55/100, DeepSeek R1 0528 53/100), so choose by what matters most for your work: Qwen3 235B-A22B Thinking 2507 for raw capability and DeepSeek R1 0528 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3 235B-A22B Thinking 2507, DeepSeek R1 0528 or GLM-4.7?

DeepSeek R1 0528 is cheaper at $0.512 input / $2.19 output per million tokens (median across 16 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 $0.932 per million tokens for DeepSeek R1 0528 versus $0.95 for Qwen3 235B-A22B Thinking 2507 (1× as much) and $1.00 for GLM-4.7 (1.1× 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 DeepSeek R1 0528 141.2 (#108 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%, DeepSeek R1 0528 76.3%; OTIS Mock AIME 2024–2025 — Qwen3 235B-A22B Thinking 2507 86.7%, GLM-4.7 83.3%, DeepSeek R1 0528 66.4%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 235B-A22B Thinking 2507, DeepSeek R1 0528 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 has the largest context window at 262,144 tokens, against 204,800 for GLM-4.7 and 163,840 for DeepSeek R1 0528. Maximum output per response: Qwen3 235B-A22B Thinking 2507 up to 81,920, DeepSeek R1 0528 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; DeepSeek R1 0528 accepts text; GLM-4.7 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 and MIT), so you can self-host them.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. Qwen3 235B-A22B Thinking 2507 came out Jul 25, 2025; DeepSeek R1 0528 came out May 28, 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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