GPT-5-Codex vs Magistral Medium vs Gemini 2.5 Computer Use Preview
GPT-5-Codex comes out ahead, 42 to 35 and 30 on our weighted score, though Magistral Medium is 20% cheaper per token.
- Our pick
OpenAIGPT-5-Codex
42/100- ECI—
- Price$1.25 / $10.00
- Context400K
Mistral AIMagistral Medium
30/100- ECI—
- Price$2.00 / $5.00
- Context128K
GoogleGemini 2.5 Computer Use Preview
35/100- ECI—
- Price$1.25 / $10.00
- Context128K
GPT-5-Codex is our pick
GPT-5-Codex is the better all-round choice, scoring 42/100 against Gemini 2.5 Computer Use Preview (35) and Magistral Medium (30). It leads on inputs & features and context window. Magistral Medium 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 priceMagistral MediumMagistral Medium $2.75 · GPT-5-Codex $3.44 · Gemini 2.5 Computer Use Preview $3.44 per 1M tokens (3:1 blend)
- Longest contextGPT-5-CodexGPT-5-Codex 400,000 · Magistral Medium 128,000 · Gemini 2.5 Computer Use Preview 128,000 tokens
- Widest inputsGPT-5-Codex and Gemini 2.5 Computer Use PreviewGPT-5-Codex: Text, Images · Magistral Medium: Text · Gemini 2.5 Computer Use Preview: Text, Images
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GPT-5-Codex | Magistral Medium | Gemini 2.5 Computer Use Preview |
|---|---|---|---|---|
| Price | 50% | 24 | 29 | 24 |
| Inputs & features | 30% | 70 | 35 | 60 |
| Context window | 20% | 44 | 24 | 24 |
| Overall | 100% | 42/100 | 30/100 | 35/100 |
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-CodexOpenAI | Magistral MediumMistral AI | Gemini 2.5 Computer Use PreviewGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.25 (best) | $2.00 | $1.25 (best) |
| Output | $10.00 | $5.00 (best) | $10.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.44 | $2.75 (best) | $3.44 |
| Long-context rate | Same rate | Same rate | Over 200K: $2.50 / $15.00 |
| Price source | Median of 3 providers | Official Mistral API | Official Google API |
| Limits | |||
| Context window | 400,000 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 128,000 tokens (best) | 16,384 tokens | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | — | magistral-medium-latest | gemini-2.5-computer-use-preview-10-2025 |
| API providers | 3 | 4 (best) | 2 |
| Released | Sep 15, 2025 | Mar 17, 2025 | Oct 7, 2025 |
| Knowledge cutoff | Sep 30, 2024 | Jun 2025 | Jan 2025 |
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-Codex$32.50
- Magistral Medium$30.00
- Gemini 2.5 Computer Use Preview$32.50
Which should you choose?
Which is better: GPT-5-Codex, Magistral Medium or Gemini 2.5 Computer Use Preview?
GPT-5-Codex is the better all-round choice, scoring 42/100 against Gemini 2.5 Computer Use Preview (35) and Magistral Medium (30). It leads on inputs & features and context window. Magistral Medium 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-Codex, Magistral Medium or Gemini 2.5 Computer Use Preview?
Magistral Medium is cheaper at $2.00 input / $5.00 output per million tokens (official Mistral API price). GPT-5-Codex costs $1.25 input / $10.00 output per million tokens (median across 3 API providers); Gemini 2.5 Computer Use Preview costs $1.25 input / $10.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $2.75 per million tokens for Magistral Medium versus $3.44 for GPT-5-Codex (1.3× as much) and $3.44 for Gemini 2.5 Computer Use Preview (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GPT-5-Codex has not been scored yet, Magistral Medium has not been scored yet and Gemini 2.5 Computer Use Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5-Codex, Magistral Medium and Gemini 2.5 Computer Use Preview 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-Codex has the largest context window at 400,000 tokens, against 128,000 for Magistral Medium and 128,000 for Gemini 2.5 Computer Use Preview. Maximum output per response: GPT-5-Codex up to 128,000, Magistral Medium up to 16,384, Gemini 2.5 Computer Use Preview up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GPT-5-Codex accepts text and images; Magistral Medium accepts text; Gemini 2.5 Computer Use Preview accepts text and images. GPT-5-Codex handles the widest range of inputs.
Are any of these open source?
No. GPT-5-Codex, Magistral Medium and Gemini 2.5 Computer Use Preview are proprietary and only available through APIs and apps.
Which is newer?
Gemini 2.5 Computer Use Preview is the newest, released Oct 7, 2025. GPT-5-Codex came out Sep 15, 2025; Magistral Medium came out Mar 17, 2025. Knowledge cutoff: GPT-5-Codex Sep 30, 2024, Magistral Medium Jun 2025, Gemini 2.5 Computer Use Preview Jan 2025.
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.
