GPT-5.2 Codex vs GPT-5.1 Chat vs Command A Translate
GPT-5.2 Codex comes out ahead, 42 to 38 and 17 on our weighted score, though GPT-5.1 Chat is 29% cheaper per token.
- Our pick
OpenAIGPT-5.2 Codex
42/100- ECI—
- Price$1.75 / $14.00
- Context400K
- OpenAI
GPT-5.1 Chat
38/100- ECI—
- Price$1.25 / $10.00
- Context128K
CohereCommand A Translate
17/100- ECI—
- Price$2.50 / $10.00
- Context8K
GPT-5.2 Codex is our pick
GPT-5.2 Codex is the better all-round choice, scoring 42/100 against GPT-5.1 Chat (38) and Command A Translate (17). It leads on inputs & features and context window. GPT-5.1 Chat wins 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 priceGPT-5.1 ChatGPT-5.1 Chat $3.44 · 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 · GPT-5.1 Chat 128,000 · Command A Translate 8,000 tokens
- Widest inputsGPT-5.2 CodexGPT-5.2 Codex: Text, Images, PDFs · GPT-5.1 Chat: Text, Images · Command A Translate: Text
- Self-hostingCommand A TranslatePublishes downloadable weights
| Measure | Weight | GPT-5.2 Codex | GPT-5.1 Chat | Command A Translate |
|---|---|---|---|---|
| Price | 50% | 18 | 24 | 19 |
| Inputs & features | 30% | 80 | 70 | 25 |
| Context window | 20% | 44 | 24 | 0 |
| Overall | 100% | 42/100 | 38/100 | 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 | GPT-5.1 ChatOpenAI | Command A TranslateCohere |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.75 | $1.25 (best) | $2.50 |
| Output | $14.00 | $10.00 (best) | $10.00 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $4.81 | $3.44 (best) | $4.38 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 2 providers | Official Cohere API |
| Limits | |||
| Context window | 400,000 tokens (best) | 128,000 tokens | 8,000 tokens |
| Max output | 128,000 tokens (best) | 16,384 tokens | 8,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | — | — | command-a-translate-08-2025 |
| API providers | 11 (best) | 2 | 1 |
| Released | Dec 11, 2025 | Nov 13, 2025 | Aug 28, 2025 |
| Knowledge cutoff | Aug 31, 2025 | Sep 30, 2024 | 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
- GPT-5.1 Chat$32.50
- Command A Translate$45.00
Which should you choose?
Which is better: GPT-5.2 Codex, GPT-5.1 Chat or Command A Translate?
GPT-5.2 Codex is the better all-round choice, scoring 42/100 against GPT-5.1 Chat (38) and Command A Translate (17). It leads on inputs & features and context window. GPT-5.1 Chat wins 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-5.2 Codex, GPT-5.1 Chat or Command A Translate?
GPT-5.1 Chat is cheaper at $1.25 input / $10.00 output per million tokens (median across 2 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 $3.44 per million tokens for GPT-5.1 Chat 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, GPT-5.1 Chat 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, GPT-5.1 Chat 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 128,000 for GPT-5.1 Chat and 8,000 for Command A Translate. Maximum output per response: GPT-5.2 Codex up to 128,000, GPT-5.1 Chat up to 16,384, 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; GPT-5.1 Chat accepts text and images; Command A Translate accepts text. GPT-5.2 Codex handles the widest range of inputs.
Are any of these open source?
Command A Translate publishes its weights and can be self-hosted; GPT-5.2 Codex and GPT-5.1 Chat is proprietary.
Which is newer?
GPT-5.2 Codex is the newest, released Dec 11, 2025. GPT-5.1 Chat came out Nov 13, 2025; Command A Translate came out Aug 28, 2025. Knowledge cutoff: GPT-5.2 Codex Aug 31, 2025, GPT-5.1 Chat Sep 30, 2024, 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.
