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Comparison · 2 models · Updated Oct 4, 2026

GLM-4.7 vs DeepSeek-V3.1

Too close to call on our weighted score (GLM-4.7 56, DeepSeek-V3.1 55). The right pick depends on what you value most.

  1. Z.ai (Zhipu)

    GLM-4.7

    Released Dec 22, 2025

    56/100
    • ECI143.5
    • Price$0.60 / $2.20
    • Context205K
    Full specs Remove GLM-4.7

  2. DeepSeek

    DeepSeek-V3.1

    Released Aug 21, 2025

    55/100
    • ECI139.9
    • Price$0.385 / $1.25
    • Context131K
    Full specs Remove DeepSeek-V3.1

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (GLM-4.7 56/100, DeepSeek-V3.1 55/100), so choose by what matters most for your work: GLM-4.7 for raw capability and DeepSeek-V3.1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGLM-4.7Capabilities Index (ECI): GLM-4.7 143.5 · DeepSeek-V3.1 139.9
  • Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
  • Longest contextGLM-4.7GLM-4.7 204,800 · DeepSeek-V3.1 131,072 tokens
  • Widest inputsSame inputsGLM-4.7: Text · DeepSeek-V3.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGLM-4.7DeepSeek-V3.1
CapabilityCapabilities Index (ECI)50%7065
Price25%5060
Inputs & features15%3535
Context window10%3224
Overall100%56/10055/100
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 DeepSeek-V3.1 specifications side by side
SpecificationGLM-4.7Z.ai (Zhipu)DeepSeek-V3.1DeepSeek
Capability
Capabilities Index (ECI)143.5 (best)139.9
ECI rank#84 of 148 (best)#100 of 148
GPQA DiamondGraduate-level science questions83.3%—
OTIS Mock AIME 2024–2025Competition mathematics83.3%—
SimpleQA VerifiedShort factual questions32.2%—
Price per million tokens
Input$0.60$0.385 (best)
Output$2.20$1.25 (best)
Cached input$0.11—
Blended (3:1)$1.00$0.601 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Z.AI APIMedian of 8 providers
Limits
Context window204,800 tokens (best)131,072 tokens
Max output131,072 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpenMIT License
API model IDglm-4.7—
API providers20 (best)8
ReleasedDec 22, 2025Aug 21, 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
  • DeepSeek-V3.1$6.35
04 — Questions

Which should you choose?

Which is better: GLM-4.7 or DeepSeek-V3.1?

It is close. Our weighted score puts them within a point (GLM-4.7 56/100, DeepSeek-V3.1 55/100), so choose by what matters most for your work: GLM-4.7 for raw capability and DeepSeek-V3.1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GLM-4.7 or DeepSeek-V3.1?

DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 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 $0.601 per million tokens for DeepSeek-V3.1 versus $1.00 for GLM-4.7 (1.7× as much).

Which scores higher on benchmarks?

GLM-4.7 scores higher on the Capabilities Index (ECI): GLM-4.7 143.5 (#84 of 148) and DeepSeek-V3.1 139.9 (#100 of 148). The confidence ranges of the top two overlap (141.3–145.6 vs 136.1–143.3), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for GLM-4.7 and DeepSeek-V3.1 yet, so there is no like-for-like coding score. On overall capability, GLM-4.7 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

GLM-4.7 has the largest context window at 204,800 tokens, against 131,072 for DeepSeek-V3.1. Maximum output per response: GLM-4.7 up to 131,072, DeepSeek-V3.1 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

GLM-4.7 accepts text; DeepSeek-V3.1 accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both publish their weights (MIT License), so you can self-host them.

Which is newer?

GLM-4.7 is the newest, released Dec 22, 2025. DeepSeek-V3.1 came out Aug 21, 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 Oct 4, 2026.

05 — Keep comparing

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