ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Kimi K2.5 vs GLM-5.1

Kimi K2.5 comes out ahead, 65 to 57 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Moonshot AI

    Kimi K2.5

    Released Jan 27, 2026

    65/100
    • ECI148.0
    • Price$0.60 / $3.00
    • Context262K
    Full specs Remove Kimi K2.5

  2. Z.ai (Zhipu)

    GLM-5.1

    Released Apr 7, 2026

    57/100
    • ECI149.9
    • Price$1.40 / $4.40
    • Context200K
    Full specs Remove GLM-5.1

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Kimi K2.5 is our pick

Kimi K2.5 is the better all-round choice, scoring 65/100 against GLM-5.1 (57). It leads on price, inputs & features and context window. GLM-5.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGLM-5.1Capabilities Index (ECI): GLM-5.1 149.9 · Kimi K2.5 148.0
  • Lowest priceKimi K2.5Kimi K2.5 $1.20 · GLM-5.1 $2.15 per 1M tokens (3:1 blend)
  • Longest contextKimi K2.5Kimi K2.5 262,144 · GLM-5.1 200,000 tokens
  • Widest inputsKimi K2.5Kimi K2.5: Text, Images, Video · GLM-5.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightKimi K2.5GLM-5.1
CapabilityCapabilities Index (ECI)50%7678
Price25%4634
Inputs & features15%8045
Context window10%3732
Overall100%65/10057/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Kimi K2.5 vs GLM-5.1 specifications side by side
SpecificationKimi K2.5Moonshot AIGLM-5.1Z.ai (Zhipu)
Capability
Capabilities Index (ECI)148.0149.9 (best)
ECI rank#58 of 148#51 of 148 (best)
GPQA DiamondGraduate-level science questions87.6%89.9% (best)
FrontierMath Tiers 1–3Research-level mathematics—36.8%
OTIS Mock AIME 2024–2025Competition mathematics92.2%93.3% (best)
SWE-bench VerifiedFixing real GitHub issues73.8%74.2% (best)
SimpleQA VerifiedShort factual questions34.3% (best)34.0%
Price per million tokens
Input$0.60 (best)$1.40
Output$3.00 (best)$4.40
Cached input—$0.26
Blended (3:1)$1.20 (best)$2.15
Long-context rateSame rateSame rate
Price sourceMedian of 21 providersOfficial Z.AI API
Limits
Context window262,144 tokens (best)200,000 tokens
Max output262,144 tokens (best)131,072 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoYesNo
ReasoningYesYes
Tool callingYesYes
Structured outputYesYes
Availability
WeightsOpenOpen
API model ID—glm-5.1
API providers2140 (best)
ReleasedJan 27, 2026Apr 7, 2026
Knowledge cutoffJan 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.

  • Kimi K2.5$12.00
  • GLM-5.1$22.80
04 — Questions

Which should you choose?

Which is better: Kimi K2.5 or GLM-5.1?

Kimi K2.5 is the better all-round choice, scoring 65/100 against GLM-5.1 (57). It leads on price, inputs & features and context window. GLM-5.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Kimi K2.5 or GLM-5.1?

Kimi K2.5 is cheaper at $0.60 input / $3.00 output per million tokens (median across 21 API providers). GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $1.20 per million tokens for Kimi K2.5 versus $2.15 for GLM-5.1 (1.8× as much).

Which scores higher on benchmarks?

GLM-5.1 scores higher on the Capabilities Index (ECI): GLM-5.1 149.9 (#51 of 148) and Kimi K2.5 148.0 (#58 of 148). The confidence ranges of the top two overlap (148.0–151.6 vs 146.5–149.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — GLM-5.1 89.9%, Kimi K2.5 87.6%; OTIS Mock AIME 2024–2025 — GLM-5.1 93.3%, Kimi K2.5 92.2%; SWE-bench Verified — GLM-5.1 74.2%, Kimi K2.5 73.8%; SimpleQA Verified — Kimi K2.5 34.3%, GLM-5.1 34.0%.

Which is better for coding?

GLM-5.1 resolves more real GitHub issues on SWE-bench Verified: GLM-5.1 74.2% and Kimi K2.5 73.8%. Both support tool calling for agent workflows.

Which has the bigger context window?

Kimi K2.5 has the largest context window at 262,144 tokens, against 200,000 for GLM-5.1. Maximum output per response: Kimi K2.5 up to 262,144, GLM-5.1 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Kimi K2.5 accepts text, images and video; GLM-5.1 accepts text. Kimi K2.5 handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

GLM-5.1 is the newest, released Apr 7, 2026. Kimi K2.5 came out Jan 27, 2026. Knowledge cutoff: Kimi K2.5 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 Oct 4, 2026.

05 — Keep comparing

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