GPT-5.5 vs Kimi K2.7 Code Highspeed vs Claude Opus 4.8
Kimi K2.7 Code Highspeed comes out ahead, 44 to 37 and 36 on our weighted score, and it is the cheaper option too.
OpenAIGPT-5.5
36/100- ECI159.2
- Price$5.00 / $30.00
- Context1.05M
- Our pick
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
AnthropicClaude Opus 4.8
37/100- ECI158.3
- Price$5.00 / $25.00
- Context1M
Kimi K2.7 Code Highspeed is our pick
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 44/100 against Claude Opus 4.8 (37) and GPT-5.5 (36). It leads on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceKimi K2.7 Code HighspeedKimi K2.7 Code Highspeed $3.42 · Claude Opus 4.8 $10.00 · GPT-5.5 $11.25 per 1M tokens (3:1 blend)
- Longest contextGPT-5.5GPT-5.5 1,050,000 · Claude Opus 4.8 1,000,000 · Kimi K2.7 Code Highspeed 262,144 tokens
- Widest inputsSame inputsGPT-5.5: Text, Images, PDFs · Kimi K2.7 Code Highspeed: Text, Images, Video · Claude Opus 4.8: Text, Images, PDFs
- Self-hostingKimi K2.7 Code HighspeedPublishes downloadable weights
| Measure | Weight | GPT-5.5 | Kimi K2.7 Code Highspeed | Claude Opus 4.8 |
|---|---|---|---|---|
| Price | 50% | 0 | 25 | 2 |
| Inputs & features | 30% | 80 | 80 | 80 |
| Context window | 20% | 61 | 37 | 60 |
| Overall | 100% | 36/100 | 44/100 | 37/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-5.5OpenAI | Kimi K2.7 Code HighspeedMoonshot AI | Claude Opus 4.8Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 159.2 (best) | — | 158.3 |
| ECI rank | #10 of 148 (best) | — | #12 of 148 |
| GPQA DiamondGraduate-level science questions | 94.0% (best) | — | 91.0% |
| FrontierMath Tiers 1–3Research-level mathematics | 85.3% (best) | — | 80.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% (best) | — | 98.3% |
| SWE-bench VerifiedFixing real GitHub issues | 80.6% | — | — |
| SimpleQA VerifiedShort factual questions | 63.0% (best) | — | 53.0% |
| Price per million tokens | |||
| Input | $5.00 | $1.90 (best) | $5.00 |
| Output | $30.00 | $8.00 (best) | $25.00 |
| Cached input | $0.50 | — | $0.50 |
| Blended (3:1) | $11.25 | $3.42 (best) | $10.00 |
| Long-context rate | Over 272K: $10.00 / $45.00 | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 11 providers | Official Anthropic API |
| Limits | |||
| Context window | 1,050,000 tokens (best) | 262,144 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens | 262,144 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yeslow · medium · high · xhigh | Yes | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gpt-5.5 | — | claude-opus-4-8 |
| API providers | 42 | 11 | 45 (best) |
| Released | Apr 23, 2026 | Jun 12, 2026 | May 28, 2026 |
| Knowledge cutoff | Dec 1, 2025 | Jan 2025 | Jan 2026 |
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 K2.7 Code Highspeed$35.00
- Claude Opus 4.8$100.00
Which should you choose?
Which is better: GPT-5.5, Kimi K2.7 Code Highspeed or Claude Opus 4.8?
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 44/100 against Claude Opus 4.8 (37) and GPT-5.5 (36). It leads on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GPT-5.5, Kimi K2.7 Code Highspeed or Claude Opus 4.8?
Kimi K2.7 Code Highspeed is cheaper at $1.90 input / $8.00 output per million tokens (median across 11 API providers). Claude Opus 4.8 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 $3.42 per million tokens for Kimi K2.7 Code Highspeed versus $10.00 for Claude Opus 4.8 (2.9× as much) and $11.25 for GPT-5.5 (3.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.5 has an ECI of 159.2, Kimi K2.7 Code Highspeed has not been scored yet and Claude Opus 4.8 has an ECI of 158.3.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K2.7 Code Highspeed and Claude Opus 4.8 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-5.5 has the largest context window at 1,050,000 tokens, against 1,000,000 for Claude Opus 4.8 and 262,144 for Kimi K2.7 Code Highspeed. Maximum output per response: GPT-5.5 up to 128,000, Kimi K2.7 Code Highspeed up to 262,144, Claude Opus 4.8 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.5 accepts text, images and PDFs; Kimi K2.7 Code Highspeed accepts text, images and video; Claude Opus 4.8 accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
Kimi K2.7 Code Highspeed publishes its weights and can be self-hosted; GPT-5.5 and Claude Opus 4.8 is proprietary.
Which is newer?
Kimi K2.7 Code Highspeed is the newest, released Jun 12, 2026. Claude Opus 4.8 came out May 28, 2026; GPT-5.5 came out Apr 23, 2026. Knowledge cutoff: GPT-5.5 Dec 1, 2025, Kimi K2.7 Code Highspeed Jan 2025, Claude Opus 4.8 Jan 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.
