GPT-4o vs Command R+ vs Mistral Large 2407
GPT-4o comes out ahead, 35 to 28 and 25 on our weighted score, though Mistral Large 2407 is 31% cheaper per token.
- Our pick
OpenAIGPT-4o
35/100- ECI129.0
- Price$2.50 / $10.00
- Context128K
CohereCommand R+
25/100- ECI—
- Price$2.50 / $10.00
- Context128K
Mistral AIMistral Large 2407
28/100- ECI127.6
- Price$2.00 / $6.00
- Context131K
GPT-4o is our pick
GPT-4o is the better all-round choice, scoring 35/100 against Mistral Large 2407 (28) and Command R+ (25). It leads on inputs & features. Mistral Large 2407 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 priceMistral Large 2407Mistral Large 2407 $3.00 · GPT-4o $4.38 · Command R+ $4.38 per 1M tokens (3:1 blend)
- Longest contextMistral Large 2407Mistral Large 2407 131,072 · GPT-4o 128,000 · Command R+ 128,000 tokens
- Widest inputsGPT-4oGPT-4o: Text, Images, PDFs · Command R+: Text · Mistral Large 2407: Text, PDFs
- Self-hostingCommand R+ and Mistral Large 2407Publishes downloadable weights
| Measure | Weight | GPT-4o | Command R+ | Mistral Large 2407 |
|---|---|---|---|---|
| Price | 50% | 19 | 19 | 26 |
| Inputs & features | 30% | 70 | 35 | 35 |
| Context window | 20% | 24 | 24 | 25 |
| Overall | 100% | 35/100 | 25/100 | 28/100 |
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-4oOpenAI | Command R+Cohere | Mistral Large 2407Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 129.0 (best) | — | 127.6 |
| ECI rank | #141 of 165 (best) | — | #144 of 165 |
| GPQA DiamondGraduate-level science questions | 48.9% | — | 49.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.3% | — | 8.5% (best) |
| Price per million tokens | |||
| Input | $2.50 | $2.50 | $2.00 (best) |
| Output | $10.00 | $10.00 | $6.00 (best) |
| Cached input | $1.25 | — | — |
| Blended (3:1) | $4.38 | $4.38 | $3.00 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Cohere API | Median of 5 providers |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 131,072 tokens (best) |
| Max output | 16,384 tokens | 4,000 tokens | 104,857 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | gpt-4o | command-r-plus-08-2024 | — |
| API providers | 26 (best) | 8 | 5 |
| Released | May 13, 2024 | Aug 30, 2024 | Jul 24, 2024 |
| Knowledge cutoff | Sep 2023 | Jun 1, 2024 | Mar 31, 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-4o$45.00
- Command R+$45.00
- Mistral Large 2407$32.00
Which should you choose?
Which is better: GPT-4o, Command R+ or Mistral Large 2407?
GPT-4o is the better all-round choice, scoring 35/100 against Mistral Large 2407 (28) and Command R+ (25). It leads on inputs & features. Mistral Large 2407 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-4o, Command R+ or Mistral Large 2407?
Mistral Large 2407 is cheaper at $2.00 input / $6.00 output per million tokens (median across 5 API providers). GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI API price); Command R+ costs $2.50 input / $10.00 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mistral Large 2407 versus $4.38 for GPT-4o (1.5× as much) and $4.38 for Command R+ (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-4o has an ECI of 129.0, Command R+ has not been scored yet and Mistral Large 2407 has an ECI of 127.6.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-4o, Command R+ and Mistral Large 2407 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?
Mistral Large 2407 has the largest context window at 131,072 tokens, against 128,000 for GPT-4o and 128,000 for Command R+. Maximum output per response: GPT-4o up to 16,384, Command R+ up to 4,000, Mistral Large 2407 up to 104,857 tokens.
Which can read images, PDFs, audio or video?
GPT-4o accepts text, images and PDFs; Command R+ accepts text; Mistral Large 2407 accepts text and PDFs. GPT-4o handles the widest range of inputs.
Are any of these open source?
Command R+ and Mistral Large 2407 publishes its weights and can be self-hosted; GPT-4o is proprietary.
Which is newer?
Command R+ is the newest, released Aug 30, 2024. Mistral Large 2407 came out Jul 24, 2024; GPT-4o came out May 13, 2024. Knowledge cutoff: GPT-4o Sep 2023, Command R+ Jun 1, 2024, Mistral Large 2407 Mar 31, 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 Nov 2, 2026.
