| Signal | Mercury Coder | Delta | Mistral Large 2407 |
|---|---|---|---|
Capabilities | 50 | -- | |
Benchmarks | 54 | -1 | |
Pricing | 99 | +5 | |
Context window size | 81 | 0 | |
Recency | 71 | +30 | |
Output Capacity | 75 | +55 | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
55.3
current score
Mistral Large 2407
right now
56.1
current score
Inception
Mistral AI
Mercury Coder saves you $437.50/month
That's $5250.00/year compared to Mistral Large 2407 at your current usage level of 100K calls/month.
| Metric | Mercury Coder | Mistral Large 2407 | Winner |
|---|---|---|---|
| Overall Score | 55 | 56 | Mistral Large 2407 |
| Rank | #144 | #142 | Mistral Large 2407 |
| Quality Rank | #144 | #142 | Mistral Large 2407 |
| Adoption Rank | #144 | #142 | Mistral Large 2407 |
| Parameters | -- | -- | -- |
| Context Window | 128K | 131K | Mistral Large 2407 |
| Pricing | $0.25/$0.75/M | $2.00/$6.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Mercury Coder |
| Benchmarks | 54 | 55 | Mistral Large 2407 |
| Pricing | 99 | 94 | Mercury Coder |
| Context window size | 81 | 81 | Mistral Large 2407 |
| Recency | 71 | 41 | Mercury Coder |
| Output Capacity | 75 | 20 | Mercury Coder |
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 55/100 (rank #144), placing it in the top 51% of all 290 models tracked.
Scores 56/100 (rank #142), placing it in the top 51% 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.
Mercury Coder offers 88% better value per quality point. At 1M tokens/day, you'd spend $15.00/month with Mercury Coder vs $120.00/month with Mistral Large 2407 - a $105.00 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Mercury Coder also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.75/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (56/100) correlates with better nuance, coherence, and style in long-form content
Mercury Coder and Mistral Large 2407 are extremely close in overall performance (only 0.8000000000000043 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Mercury Coder
Marginally better benchmark scores; both are excellent
Best for Cost
Mercury Coder
88% lower pricing; better value at scale
Best for Reliability
Mercury Coder
Higher uptime and faster response speeds
Best for Prototyping
Mercury Coder
Stronger community support and better developer experience
Best for Production
Mercury Coder
Wider enterprise adoption and proven at scale
by Inception
| Capability | Mercury Coder | Mistral Large 2407 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Inception
Mistral AI
Mercury Coder saves you $9.45/month
That's 88% cheaper than Mistral Large 2407 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 | Mercury Coder | Mistral Large 2407 |
|---|---|---|
| Context Window | 128K | 131K |
| Max Output Tokens | 32,000 | -- |
| Open Source | No | No |
| Created | Apr 30, 2025 | Nov 19, 2024 |
Mistral Large 2407 scores 56/100 (rank #142) compared to Mercury Coder's 55/100 (rank #144), giving it a 1-point advantage. Mistral Large 2407 is the stronger overall choice, though Mercury Coder may excel in specific areas like cost efficiency.
Mercury Coder is ranked #144 and Mistral Large 2407 is ranked #142 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Mercury Coder is cheaper at $0.75/M output tokens vs Mistral Large 2407's $6.00/M output tokens - 8.0x more expensive. Input token pricing: Mercury Coder at $0.25/M vs Mistral Large 2407 at $2.00/M.
Mistral Large 2407 has a larger context window of 131,072 tokens compared to Mercury Coder's 128,000 tokens. A larger context window means the model can process longer documents and conversations.