| Signal | GPT-4o (2024-05-13) | Delta | Mercury 2 |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 59 | 0 | |
Pricing | 15 | +14 | |
Context window size | 81 | -- | |
Recency | 7 | -93 | |
Output Capacity | 60 | -18 | |
| Overall Result | 1 wins | of 6 | 3 wins |
6
days higher
3
days
21
days higher
OpenAI
Inception
Mercury 2 saves you $1187.50/month
That's $14250.00/year compared to GPT-4o (2024-05-13) at your current usage level of 100K calls/month.
| Metric | GPT-4o (2024-05-13) | Mercury 2 | Winner |
|---|---|---|---|
| Overall Score | 61 | 61 | Mercury 2 |
| Rank | #95 | #94 | Mercury 2 |
| Quality Rank | #95 | #94 | Mercury 2 |
| Adoption Rank | #95 | #94 | Mercury 2 |
| Parameters | -- | -- | -- |
| Context Window | 128K | 128K | -- |
| Pricing | $5.00/$15.00/M | $0.25/$0.75/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | GPT-4o (2024-05-13) |
| Benchmarks | 59 | 60 | Mercury 2 |
| Pricing | 15 | 1 | GPT-4o (2024-05-13) |
| Context window size | 81 | 81 | GPT-4o (2024-05-13) |
| Recency | 7 | 100 | Mercury 2 |
| Output Capacity | 60 | 78 | Mercury 2 |
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%). Here's what the scores mean for these two models:
Scores 61/100 (rank #95), placing it in the top 68% of all 290 models tracked.
Scores 61/100 (rank #94), placing it in the top 68% of all 290 models tracked.
With only a 0-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 2 offers 95% better value per quality point. At 1M tokens/day, you'd spend $15.00/month with Mercury 2 vs $300.00/month with GPT-4o (2024-05-13) - a $285.00 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 2 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 ($0.75/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (61/100) 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-4o (2024-05-13) and Mercury 2 are extremely close in overall performance (only 0.20000000000000284 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4o (2024-05-13)
Marginally better benchmark scores; both are excellent
Best for Cost
Mercury 2
95% lower pricing; better value at scale
Best for Reliability
GPT-4o (2024-05-13)
Higher uptime and faster response speeds
Best for Prototyping
GPT-4o (2024-05-13)
Stronger community support and better developer experience
Best for Production
GPT-4o (2024-05-13)
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4o (2024-05-13) | Mercury 2 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
Inception
Mercury 2 saves you $25.65/month
That's 95% cheaper than GPT-4o (2024-05-13) 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-4o (2024-05-13) | Mercury 2 |
|---|---|---|
| Context Window | 128K | 128K |
| Max Output Tokens | 4,096 | 50,000 |
| Open Source | No | No |
| Created | May 13, 2024 | Mar 4, 2026 |
Mercury 2 scores 61/100 (rank #94) compared to GPT-4o (2024-05-13)'s 61/100 (rank #95), giving it a 0-point advantage. Mercury 2 is the stronger overall choice, though GPT-4o (2024-05-13) may excel in specific areas like certain benchmarks.
GPT-4o (2024-05-13) is ranked #95 and Mercury 2 is ranked #94 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 2 is cheaper at $0.75/M output tokens vs GPT-4o (2024-05-13)'s $15.00/M output tokens - 20.0x more expensive. Input token pricing: GPT-4o (2024-05-13) at $5.00/M vs Mercury 2 at $0.25/M.
GPT-4o (2024-05-13) has a larger context window of 128,000 tokens compared to Mercury 2's 128,000 tokens. A larger context window means the model can process longer documents and conversations.