GPT-5.2 Codex vs Kimi K2.7 Code Highspeed vs Command A Translate
Too close to call on our weighted score (Kimi K2.7 Code Highspeed 44, GPT-5.2 Codex 42, Command A Translate 17). The right pick depends on what you value most.
OpenAIGPT-5.2 Codex
42/100- ECI—
- Price$1.75 / $14.00
- Context400K
Moonshot AIKimi K2.7 Code Highspeed
44/100- ECI—
- Price$1.90 / $8.00
- Context262K
CohereCommand A Translate
17/100- ECI—
- Price$2.50 / $10.00
- Context8K
Too close to call
It is close. Our weighted score puts them within 2 points (Kimi K2.7 Code Highspeed 44/100, GPT-5.2 Codex 42/100, Command A Translate 17/100), so choose by what matters most for your work: Kimi K2.7 Code Highspeed on price and GPT-5.2 Codex for long inputs. 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 Codex $4.81 per 1M tokens (3:1 blend)
- Longest contextGPT-5.2 CodexGPT-5.2 Codex 400,000 · Kimi K2.7 Code Highspeed 262,144 · Command A Translate 8,000 tokens
- Widest inputsGPT-5.2 Codex and Kimi K2.7 Code HighspeedGPT-5.2 Codex: Text, Images, PDFs · 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 Codex | Kimi K2.7 Code Highspeed | Command A Translate |
|---|---|---|---|---|
| Price | 50% | 18 | 25 | 19 |
| Inputs & features | 30% | 80 | 80 | 25 |
| Context window | 20% | 44 | 37 | 0 |
| Overall | 100% | 42/100 | 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 | GPT-5.2 CodexOpenAI | Kimi K2.7 Code HighspeedMoonshot AI | Command A TranslateCohere |
|---|---|---|---|
| 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 | — | — | — |
| Blended (3:1) | $4.81 | $3.42 (best) | $4.38 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 11 providers | Official Cohere API |
| Limits | |||
| Context window | 400,000 tokens (best) | 262,144 tokens | 8,000 tokens |
| Max output | 128,000 tokens | 262,144 tokens (best) | 8,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | command-a-translate-08-2025 |
| API providers | 11 (best) | 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 Codex$45.50
- Kimi K2.7 Code Highspeed$35.00
- Command A Translate$45.00
Which should you choose?
Which is better: GPT-5.2 Codex, Kimi K2.7 Code Highspeed or Command A Translate?
It is close. Our weighted score puts them within 2 points (Kimi K2.7 Code Highspeed 44/100, GPT-5.2 Codex 42/100, Command A Translate 17/100), so choose by what matters most for your work: Kimi K2.7 Code Highspeed on price and GPT-5.2 Codex for long inputs. 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 Codex, 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 Codex costs $1.75 input / $14.00 output per million tokens (median across 11 API providers). 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 Codex (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5.2 Codex 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 Codex, 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?
GPT-5.2 Codex has the largest context window at 400,000 tokens, against 262,144 for Kimi K2.7 Code Highspeed and 8,000 for Command A Translate. Maximum output per response: GPT-5.2 Codex up to 128,000, 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 Codex accepts text, images and PDFs; Kimi K2.7 Code Highspeed accepts text, images and video; Command A Translate accepts text. GPT-5.2 Codex 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 Codex is proprietary.
Which is newer?
Kimi K2.7 Code Highspeed is the newest, released Jun 12, 2026. GPT-5.2 Codex came out Dec 11, 2025; Command A Translate came out Aug 28, 2025. Knowledge cutoff: GPT-5.2 Codex 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.
