ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GPT-5.5 vs Kimi K3 vs Claude Opus 4.7

Too close to call on our weighted score (Kimi K3 65, GPT-5.5 63, Claude Opus 4.7 62). The right pick depends on what you value most.

  1. OpenAI

    GPT-5.5

    Released Apr 23, 2026

    63/100
    • ECI159.2
    • Price$5.00 / $30.00
    • Context1.05M
  2. Moonshot AI

    Kimi K3

    Released Jul 16, 2026

    65/100
    • ECI157.6
    • Price$3.00 / $15.00
    • Context1.05M
  3. Anthropic

    Claude Opus 4.7

    Released Apr 16, 2026

    62/100
    • ECI156.4
    • Price$5.00 / $25.00
    • Context1M
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Kimi K3 65/100, GPT-5.5 63/100, Claude Opus 4.7 62/100), so choose by what matters most for your work: GPT-5.5 for raw capability and Kimi K3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5.5Capabilities Index (ECI): GPT-5.5 159.2 · Kimi K3 157.6 · Claude Opus 4.7 156.4
  • Lowest priceKimi K3Kimi K3 $6.00 · Claude Opus 4.7 $10.00 · GPT-5.5 $11.25 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.5 and Kimi K3GPT-5.5 1,050,000 · Kimi K3 1,048,576 · Claude Opus 4.7 1,000,000 tokens
  • Widest inputsSame inputsGPT-5.5: Text, Images, PDFs · Kimi K3: Text, Images, Video · Claude Opus 4.7: Text, Images, PDFs
  • Self-hostingKimi K3Publishes downloadable weights
How the score is built
MeasureWeightGPT-5.5Kimi K3Claude Opus 4.7
CapabilityCapabilities Index (ECI)50%908886
Price25%0132
Inputs & features15%808080
Context window10%616160
Overall100%63/10065/10062/100
02 — Side by side

Every spec in one table

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

GPT-5.5 vs Kimi K3 vs Claude Opus 4.7 specifications side by side
SpecificationGPT-5.5OpenAIKimi K3Moonshot AIClaude Opus 4.7Anthropic
Capability
Capabilities Index (ECI)159.2 (best)157.6156.4
ECI rank#10 of 148 (best)#13 of 148#22 of 148
GPQA DiamondGraduate-level science questions94.0% (best)93.1%90.2%
FrontierMath Tiers 1–3Research-level mathematics85.3% (best)72.2%70.2%
OTIS Mock AIME 2024–2025Competition mathematics100% (best)97.2%97.8%
SWE-bench VerifiedFixing real GitHub issues80.6%—83.5% (best)
SimpleQA VerifiedShort factual questions63.0% (best)50.6%51.7%
Price per million tokens
Input$5.00$3.00 (best)$5.00
Output$30.00$15.00 (best)$25.00
Cached input$0.50$0.30 (best)$0.50
Blended (3:1)$11.25$6.00 (best)$10.00
Long-context rateOver 272K: $10.00 / $45.00Same rateSame rate
Price sourceOfficial OpenAI APIOfficial Moonshot AI APIOfficial Anthropic API
Limits
Context window1,050,000 tokens (best)1,048,576 tokens1,000,000 tokens
Max output128,000 tokens131,072 tokens (best)128,000 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesNoYes
AudioNoNoNo
VideoNoYesNo
ReasoningYeslow · medium · high · xhighYeslow · high · maxYeslow · medium · high · xhigh · max
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryOpenProprietary
API model IDgpt-5.5kimi-k3claude-opus-4-7
API providers4268 (best)38
ReleasedApr 23, 2026Jul 16, 2026Apr 16, 2026
Knowledge cutoffDec 1, 2025—Jan 31, 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.

  • GPT-5.5$110.00
  • Kimi K3$60.00
  • Claude Opus 4.7$100.00
04 — Questions

Which should you choose?

Which is better: GPT-5.5, Kimi K3 or Claude Opus 4.7?

It is close. Our weighted score puts them within 2 points (Kimi K3 65/100, GPT-5.5 63/100, Claude Opus 4.7 62/100), so choose by what matters most for your work: GPT-5.5 for raw capability and Kimi K3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-5.5, Kimi K3 or Claude Opus 4.7?

Kimi K3 is cheaper at $3.00 input / $15.00 output per million tokens (official Moonshot AI API price). Claude Opus 4.7 costs $5.00 input / $25.00 output per million tokens (official Anthropic API price); GPT-5.5 costs $5.00 input / $30.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $6.00 per million tokens for Kimi K3 versus $10.00 for Claude Opus 4.7 (1.7× as much) and $11.25 for GPT-5.5 (1.9× as much).

Which scores higher on benchmarks?

GPT-5.5 scores higher on the Capabilities Index (ECI): GPT-5.5 159.2 (#10 of 148), Kimi K3 157.6 (#13 of 148) and Claude Opus 4.7 156.4 (#22 of 148). The confidence ranges of the top two overlap (156.9–162.4 vs 154.9–160.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-5.5 94.0%, Kimi K3 93.1%, Claude Opus 4.7 90.2%; FrontierMath Tiers 1–3 — GPT-5.5 85.3%, Kimi K3 72.2%, Claude Opus 4.7 70.2%; OTIS Mock AIME 2024–2025 — GPT-5.5 100%, Claude Opus 4.7 97.8%, Kimi K3 97.2%; SimpleQA Verified — GPT-5.5 63.0%, Claude Opus 4.7 51.7%, Kimi K3 50.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K3 yet, so there is no like-for-like coding score. On overall capability, GPT-5.5 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?

GPT-5.5 and Kimi K3 have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for Claude Opus 4.7. Maximum output per response: GPT-5.5 up to 128,000, Kimi K3 up to 131,072, Claude Opus 4.7 up to 128,000 tokens.

Which can read images, PDFs, audio or video?

GPT-5.5 accepts text, images and PDFs; Kimi K3 accepts text, images and video; Claude Opus 4.7 accepts text, images and PDFs. They handle the same number of input types.

Are any of these open source?

Kimi K3 publishes its weights and can be self-hosted; GPT-5.5 and Claude Opus 4.7 is proprietary.

Which is newer?

Kimi K3 is the newest, released Jul 16, 2026. GPT-5.5 came out Apr 23, 2026; Claude Opus 4.7 came out Apr 16, 2026. Knowledge cutoff: GPT-5.5 Dec 1, 2025, Claude Opus 4.7 Jan 31, 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.