ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GLM-5.1 vs Kimi K2.7 Code vs Claude Opus 5

Too close to call on our weighted score (Claude Opus 5 66, Kimi K2.7 Code 64, GLM-5.1 57). The right pick depends on what you value most.

  1. Z.ai (Zhipu)

    GLM-5.1

    Released Apr 7, 2026

    57/100
    • ECI149.9
    • Price$1.40 / $4.40
    • Context200K
  2. Moonshot AI

    Kimi K2.7 Code

    Released Jun 12, 2026

    64/100
    • ECI150.0
    • Price$0.95 / $4.00
    • Context262K
  3. Anthropic

    Claude Opus 5

    Released Jul 24, 2026

    66/100
    • ECI162.9
    • Price$5.00 / $25.00
    • Context1M
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Claude Opus 5 66/100, Kimi K2.7 Code 64/100, GLM-5.1 57/100), so choose by what matters most for your work: Claude Opus 5 for raw capability and Kimi K2.7 Code on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityClaude Opus 5Capabilities Index (ECI): Claude Opus 5 162.9 · Kimi K2.7 Code 150.0 · GLM-5.1 149.9
  • Lowest priceKimi K2.7 CodeKimi K2.7 Code $1.71 · GLM-5.1 $2.15 · Claude Opus 5 $10.00 per 1M tokens (3:1 blend)
  • Longest contextClaude Opus 5Claude Opus 5 1,000,000 · Kimi K2.7 Code 262,144 · GLM-5.1 200,000 tokens
  • Widest inputsKimi K2.7 Code and Claude Opus 5GLM-5.1: Text · Kimi K2.7 Code: Text, Images, Video · Claude Opus 5: Text, Images, PDFs
  • Self-hostingGLM-5.1 and Kimi K2.7 CodePublishes downloadable weights
How the score is built
MeasureWeightGLM-5.1Kimi K2.7 CodeClaude Opus 5
CapabilityCapabilities Index (ECI)50%787894
Price25%34392
Inputs & features15%458080
Context window10%323760
Overall100%57/10064/10066/100
02 — Side by side

Every spec in one table

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

GLM-5.1 vs Kimi K2.7 Code vs Claude Opus 5 specifications side by side
SpecificationGLM-5.1Z.ai (Zhipu)Kimi K2.7 CodeMoonshot AIClaude Opus 5Anthropic
Capability
Capabilities Index (ECI)149.9150.0162.9 (best)
ECI rank#51 of 148#49 of 148#5 of 148 (best)
GPQA DiamondGraduate-level science questions89.9%87.9%93.9% (best)
FrontierMath Tiers 1–3Research-level mathematics36.8%54.0%85.6% (best)
OTIS Mock AIME 2024–2025Competition mathematics93.3%95.6%98.9% (best)
SWE-bench VerifiedFixing real GitHub issues74.2%——
SimpleQA VerifiedShort factual questions34.0%36.5%59.9% (best)
Price per million tokens
Input$1.40$0.95 (best)$5.00
Output$4.40$4.00 (best)$25.00
Cached input$0.26$0.19 (best)$0.50
Blended (3:1)$2.15$1.71 (best)$10.00
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Z.AI APIOfficial Moonshot AI APIOfficial Anthropic API
Limits
Context window200,000 tokens262,144 tokens1,000,000 tokens (best)
Max output131,072 tokens262,144 tokens (best)128,000 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoNoYes
AudioNoNoNo
VideoNoYesNo
ReasoningYesYesYeslow · medium · high · xhigh · max
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsOpenOpenProprietary
API model IDglm-5.1kimi-k2.7-codeclaude-opus-5
API providers4051 (best)35
ReleasedApr 7, 2026Jun 12, 2026Jul 24, 2026
Knowledge cutoff—Jan 2025May 2026
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-5.1$22.80
  • Kimi K2.7 Code$17.50
  • Claude Opus 5$100.00
04 — Questions

Which should you choose?

Which is better: GLM-5.1, Kimi K2.7 Code or Claude Opus 5?

It is close. Our weighted score puts them within 1 points (Claude Opus 5 66/100, Kimi K2.7 Code 64/100, GLM-5.1 57/100), so choose by what matters most for your work: Claude Opus 5 for raw capability and Kimi K2.7 Code on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GLM-5.1, Kimi K2.7 Code or Claude Opus 5?

Kimi K2.7 Code is cheaper at $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). GLM-5.1 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price); Claude Opus 5 costs $5.00 input / $25.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $1.71 per million tokens for Kimi K2.7 Code versus $2.15 for GLM-5.1 (1.3× as much) and $10.00 for Claude Opus 5 (5.8× as much).

Which scores higher on benchmarks?

Claude Opus 5 scores higher on the Capabilities Index (ECI): Claude Opus 5 162.9 (#5 of 148), Kimi K2.7 Code 150.0 (#49 of 148) and GLM-5.1 149.9 (#51 of 148). Their confidence ranges do not overlap (160.2–166.7 vs 148.1–151.8), so the gap is a real one. On individual benchmarks: GPQA Diamond — Claude Opus 5 93.9%, GLM-5.1 89.9%, Kimi K2.7 Code 87.9%; FrontierMath Tiers 1–3 — Claude Opus 5 85.6%, Kimi K2.7 Code 54.0%, GLM-5.1 36.8%; OTIS Mock AIME 2024–2025 — Claude Opus 5 98.9%, Kimi K2.7 Code 95.6%, GLM-5.1 93.3%; SimpleQA Verified — Claude Opus 5 59.9%, Kimi K2.7 Code 36.5%, GLM-5.1 34.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2.7 Code and Claude Opus 5 yet, so there is no like-for-like coding score. On overall capability, Claude Opus 5 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?

Claude Opus 5 has the largest context window at 1,000,000 tokens, against 262,144 for Kimi K2.7 Code and 200,000 for GLM-5.1. Maximum output per response: GLM-5.1 up to 131,072, Kimi K2.7 Code up to 262,144, Claude Opus 5 up to 128,000 tokens.

Which can read images, PDFs, audio or video?

GLM-5.1 accepts text; Kimi K2.7 Code accepts text, images and video; Claude Opus 5 accepts text, images and PDFs. Kimi K2.7 Code handles the widest range of inputs.

Are any of these open source?

GLM-5.1 and Kimi K2.7 Code publishes its weights and can be self-hosted; Claude Opus 5 is proprietary.

Which is newer?

Claude Opus 5 is the newest, released Jul 24, 2026. Kimi K2.7 Code came out Jun 12, 2026; GLM-5.1 came out Apr 7, 2026. Knowledge cutoff: Kimi K2.7 Code Jan 2025, Claude Opus 5 May 2026.

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.