| Signal | GPT-4 | Delta | Mistral Large |
|---|---|---|---|
Capabilities | 50 | -- | |
Benchmarks | 66 | -2 | |
Pricing | 40 | -54 | |
Context window size | 56 | -17 | |
Recency | 0 | -- | |
Output Capacity | 60 | +40 | |
| Overall Result | 1 wins | of 6 | 3 wins |
Score History
64.5
current score
Mistral Large
right now
65.5
current score
OpenAI
Mistral AI
Mistral Large saves you $5500.00/month
That's $66000.00/year compared to GPT-4 at your current usage level of 100K calls/month.
| Metric | GPT-4 | Mistral Large | Winner |
|---|---|---|---|
| Overall Score | 65 | 66 | Mistral Large |
| Rank | #126 | #120 | Mistral Large |
| Quality Rank | #126 | #120 | Mistral Large |
| Adoption Rank | #126 | #120 | Mistral Large |
| Parameters | -- | -- | -- |
| Context Window | 8K | 128K | Mistral Large |
| Pricing | $30.00/$60.00/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | GPT-4 |
| Benchmarks | 66 | 68 | Mistral Large |
| Pricing | 40 | 94 | Mistral Large |
| Context window size | 56 | 73 | Mistral Large |
| Recency | 0 | 0 | GPT-4 |
| Output Capacity | 60 | 20 | GPT-4 |
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 65/100 (rank #126), placing it in the top 57% of all 290 models tracked.
Scores 66/100 (rank #120), placing it in the top 59% of all 290 models tracked.
With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Mistral Large offers 91% better value per quality point. At 1M tokens/day, you'd spend $120.00/month with Mistral Large vs $1350.00/month with GPT-4 - a $1230.00 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 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K 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 (66/100) correlates with better nuance, coherence, and style in long-form content
GPT-4 and Mistral Large are extremely close in overall performance (only 1 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Large
91% lower pricing; better value at scale
Best for Reliability
GPT-4
Higher uptime and faster response speeds
Best for Prototyping
GPT-4
Stronger community support and better developer experience
Best for Production
GPT-4
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4 | Mistral Large |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Mistral AI
Mistral Large saves you $115.20/month
That's 91% cheaper than GPT-4 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-4 | Mistral Large |
|---|---|---|
| Context Window | 8K | 128K |
| Max Output Tokens | 4,096 | -- |
| Open Source | No | No |
| Created | May 28, 2023 | Feb 26, 2024 |