| Signal | GPT-5.2-Codex | Delta | Mistral Large 2407 |
|---|---|---|---|
Capabilities | 83 | +33 | |
Benchmarks | 89 | +34 | |
Pricing | 86 | -8 | |
Context window size | 89 | +8 | |
Recency | 100 | +65 | |
Output Capacity | 85 | +65 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
89.7
current score
GPT-5.2-Codex
right now
56.1
current score
OpenAI
Mistral AI
Mistral Large 2407 saves you $375.00/month
That's $4500.00/year compared to GPT-5.2-Codex at your current usage level of 100K calls/month.
| Metric | GPT-5.2-Codex | Mistral Large 2407 | Winner |
|---|---|---|---|
| Overall Score | 90 | 56 | GPT-5.2-Codex |
| Rank | #6 | #160 | GPT-5.2-Codex |
| Quality Rank | #6 | #160 | GPT-5.2-Codex |
| Adoption Rank | #6 | #160 | GPT-5.2-Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 131K | GPT-5.2-Codex |
| Pricing | $1.75/$14.00/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 50 | GPT-5.2-Codex |
| Benchmarks | 89 | 55 | GPT-5.2-Codex |
| Pricing | 86 | 94 | Mistral Large 2407 |
| Context window size | 89 | 81 | GPT-5.2-Codex |
| Recency | 100 | 35 | GPT-5.2-Codex |
| Output Capacity | 85 | 20 | GPT-5.2-Codex |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 90/100 (rank #6), placing it in the top 98% of all 290 models tracked.
Scores 56/100 (rank #160), placing it in the top 45% of all 290 models tracked.
GPT-5.2-Codex has a 34-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Mistral Large 2407 offers 49% better value per quality point. At 1M tokens/day, you'd spend $120.00/month with Mistral Large 2407 vs $236.25/month with GPT-5.2-Codex - a $116.25 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Mistral Large 2407 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($6.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (90/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-5.2-Codex clearly outperforms Mistral Large 2407 with a significant 33.6-point lead. For most general use cases, GPT-5.2-Codex is the stronger choice. However, Mistral Large 2407 may still excel in niche scenarios.
Best for Quality
GPT-5.2-Codex
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Large 2407
49% lower pricing; better value at scale
Best for Reliability
GPT-5.2-Codex
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.2-Codex
Stronger community support and better developer experience
Best for Production
GPT-5.2-Codex
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.2-Codex | Mistral Large 2407 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Mistral AI
Mistral Large 2407 saves you $9.15/month
That's 46% cheaper than GPT-5.2-Codex at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-5.2-Codex | Mistral Large 2407 |
|---|---|---|
| Context Window | 400K | 131K |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | No |
| Created | Jan 14, 2026 | Nov 19, 2024 |