| Signal | GPT-4o-mini | Delta | Llama 4 Maverick |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 77 | +7 | |
Pricing | 99 | -- | |
Context window size | 81 | -14 | |
Recency | 19 | -48 | |
Output Capacity | 70 | -- | |
| Overall Result | 1 wins | of 6 | 2 wins |
Score History
70.4
current score
GPT-4o-mini
right now
67.9
current score
OpenAI
Meta
| Metric | GPT-4o-mini | Llama 4 Maverick | Winner |
|---|---|---|---|
| Overall Score | 70 | 68 | GPT-4o-mini |
| Rank | #52 | #66 | GPT-4o-mini |
| Quality Rank | #52 | #66 | GPT-4o-mini |
| Adoption Rank | #52 | #66 | GPT-4o-mini |
| Parameters | -- | -- | -- |
| Context Window | 128K | 1049K | Llama 4 Maverick |
| Pricing | $0.15/$0.60/M | $0.15/$0.60/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | GPT-4o-mini |
| Benchmarks | 77 | 70 | GPT-4o-mini |
| Pricing | 99 | 99 | GPT-4o-mini |
| Context window size | 81 | 96 | Llama 4 Maverick |
| Recency | 19 | 67 | Llama 4 Maverick |
| Output Capacity | 70 | 70 | GPT-4o-mini |
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 70/100 (rank #52), placing it in the top 82% of all 290 models tracked.
Scores 68/100 (rank #66), placing it in the top 78% of all 290 models tracked.
With only a 3-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.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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. GPT-4o-mini also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.60/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (70/100) 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-mini and Llama 4 Maverick are extremely close in overall performance (only 2.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4o-mini
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-4o-mini
0% lower pricing; better value at scale
Best for Reliability
GPT-4o-mini
Higher uptime and faster response speeds
Best for Prototyping
GPT-4o-mini
Stronger community support and better developer experience
Best for Production
GPT-4o-mini
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4o-mini | Llama 4 Maverick |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Meta
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-4o-mini | Llama 4 Maverick |
|---|---|---|
| Context Window | 128K | 1.0M |
| Max Output Tokens | 16,384 | 16,384 |
| Open Source | No | Yes |
| Created | Jul 18, 2024 | Apr 5, 2025 |
GPT-4o-mini scores 70/100 (rank #52) compared to Llama 4 Maverick's 68/100 (rank #66), giving it a 3-point advantage. GPT-4o-mini is the stronger overall choice, though Llama 4 Maverick may excel in specific areas like certain benchmarks.
GPT-4o-mini is ranked #52 and Llama 4 Maverick is ranked #66 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.
GPT-4o-mini is cheaper at $0.60/M output tokens vs Llama 4 Maverick's $0.60/M output tokens - 1.0x more expensive. Input token pricing: GPT-4o-mini at $0.15/M vs Llama 4 Maverick at $0.15/M.
Llama 4 Maverick has a larger context window of 1,048,576 tokens compared to GPT-4o-mini's 128,000 tokens. A larger context window means the model can process longer documents and conversations.