GPT-5.2 Chat vs Kimi K2.7 Code Highspeed vs Command A Translate
Kimi K2.7 Code Highspeed comes out ahead, 44 to 35 and 17 on our weighted score, and it is the cheaper option too.
OpenAI
GPT-5.2 Chat
35/100- ECI—
- Price$1.75 / $14.00
- Context128K
- Our pick
Moonshot AI
Kimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
Cohere
Command A Translate
17/100- ECI—
- Price$2.50 / $10.00
- Context8K
Kimi K2.7 Code Highspeed is our pick
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 44/100 against GPT-5.2 Chat (35) and Command A Translate (17). It leads on price, inputs & features and context window. 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 · Command A Translate $4.38 · GPT-5.2 Chat $4.81 per 1M tokens (3:1 blend)
- Longest contextKimi K2.7 Code HighspeedKimi K2.7 Code Highspeed 262,144 · GPT-5.2 Chat 128,000 · Command A Translate 8,000 tokens
- Widest inputsKimi K2.7 Code HighspeedGPT-5.2 Chat: Text, Images · Kimi K2.7 Code Highspeed: Text, Images, Video · Command A Translate: Text
- Self-hostingKimi K2.7 Code Highspeed and Command A TranslatePublishes downloadable weights
| Measure | Weight | GPT-5.2 Chat | Kimi K2.7 Code Highspeed | Command A Translate |
|---|---|---|---|---|
| Price | 50% | 18 | 25 | 19 |
| Inputs & features | 30% | 70 | 80 | 25 |
| Context window | 20% | 24 | 37 | 0 |
| Overall | 100% | 35/100 | 44/100 | 17/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.75 (best) | $1.90 | $2.50 |
| Output | $14.00 | $8.00 (best) | $10.00 |
| Cached input | $0.175 | — | — |
| Blended (3:1) | $4.81 | $3.42 (best) | $4.38 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 11 providers | Official Cohere API |
| Limits | |||
| Context window | 128,000 tokens | 262,144 tokens (best) | 8,000 tokens |
| Max output | 16,384 tokens | 262,144 tokens (best) | 8,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yesmedium | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | gpt-5.2-chat-latest | — | command-a-translate-08-2025 |
| API providers | 3 | 11 (best) | 1 |
| Released | Dec 11, 2025 | Jun 12, 2026 | Aug 28, 2025 |
| Knowledge cutoff | Aug 31, 2025 | Jan 2025 | Jun 1, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
GPT-5.2 Chat$45.50
Kimi K2.7 Code Highspeed$35.00
Command A Translate$45.00
Which should you choose?
Which is better: GPT-5.2 Chat, Kimi K2.7 Code Highspeed or Command A Translate?
Kimi K2.7 Code Highspeed is the better all-round choice, scoring 44/100 against GPT-5.2 Chat (35) and Command A Translate (17). It leads on price, inputs & features and context window. 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-5.2 Chat, Kimi K2.7 Code Highspeed or Command A Translate?
Kimi K2.7 Code Highspeed is cheaper at $1.90 input / $8.00 output per million tokens (median across 11 API providers). Command A Translate costs $2.50 input / $10.00 output per million tokens (official Cohere API price); GPT-5.2 Chat costs $1.75 input / $14.00 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 $4.38 for Command A Translate (1.3× as much) and $4.81 for GPT-5.2 Chat (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.2 Chat has not been scored yet, Kimi K2.7 Code Highspeed has not been scored yet and Command A Translate has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.2 Chat, Kimi K2.7 Code Highspeed and Command A Translate 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?
Kimi K2.7 Code Highspeed has the largest context window at 262,144 tokens, against 128,000 for GPT-5.2 Chat and 8,000 for Command A Translate. Maximum output per response: GPT-5.2 Chat up to 16,384, Kimi K2.7 Code Highspeed up to 262,144, Command A Translate up to 8,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5.2 Chat accepts text and images; Kimi K2.7 Code Highspeed accepts text, images and video; Command A Translate accepts text. Kimi K2.7 Code Highspeed handles the widest range of inputs.
Are any of these open source?
Kimi K2.7 Code Highspeed and Command A Translate publishes its weights and can be self-hosted; GPT-5.2 Chat is proprietary.
Which is newer?
Kimi K2.7 Code Highspeed is the newest, released Jun 12, 2026. GPT-5.2 Chat came out Dec 11, 2025; Command A Translate came out Aug 28, 2025. Knowledge cutoff: GPT-5.2 Chat Aug 31, 2025, Kimi K2.7 Code Highspeed Jan 2025, Command A Translate Jun 1, 2024.
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.