| Signal | GPT-4.1 Mini | Delta | Llama 3.1 8B Instruct |
|---|---|---|---|
Capabilities | 83 | +33 | |
Benchmarks | 51 | 0 | |
Pricing | 98 | -2 | |
Context window size | 96 | +29 | |
Recency | 68 | +48 | |
Output Capacity | 75 | +5 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
53.6
current score
GPT-4.1 Mini
right now
52.1
current score
OpenAI
Meta
Llama 3.1 8B Instruct saves you $115.50/month
That's $1386.00/year compared to GPT-4.1 Mini at your current usage level of 100K calls/month.
| Metric | GPT-4.1 Mini | Llama 3.1 8B Instruct | Winner |
|---|---|---|---|
| Overall Score | 54 | 52 | GPT-4.1 Mini |
| Rank | #108 | #110 | GPT-4.1 Mini |
| Quality Rank | #108 | #110 | GPT-4.1 Mini |
| Adoption Rank | #108 | #110 | GPT-4.1 Mini |
| Parameters | -- | 8B | -- |
| Context Window | 1048K | 16K | GPT-4.1 Mini |
| Pricing | $0.40/$1.60/M | $0.02/$0.05/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 50 | GPT-4.1 Mini |
| Benchmarks | 51 | 51 | Llama 3.1 8B Instruct |
| Pricing | 98 | 100 | Llama 3.1 8B Instruct |
| Context window size | 96 | 67 | GPT-4.1 Mini |
| Recency | 68 | 20 | GPT-4.1 Mini |
| Output Capacity | 75 | 70 | GPT-4.1 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 54/100 (rank #108), placing it in the top 63% of all 290 models tracked.
Scores 52/100 (rank #110), placing it in the top 62% of all 290 models tracked.
With only a 2-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.
Llama 3.1 8B Instruct offers 97% better value per quality point. At 1M tokens/day, you'd spend $1.05/month with Llama 3.1 8B Instruct vs $30.00/month with GPT-4.1 Mini - a $28.95 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. Llama 3.1 8B Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1048K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.05/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (54/100) 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-4.1 Mini and Llama 3.1 8B Instruct are extremely close in overall performance (only 1.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-4.1 Mini
Marginally better benchmark scores; both are excellent
Best for Cost
Llama 3.1 8B Instruct
97% lower pricing; better value at scale
Best for Reliability
GPT-4.1 Mini
Higher uptime and faster response speeds
Best for Prototyping
GPT-4.1 Mini
Stronger community support and better developer experience
Best for Production
GPT-4.1 Mini
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4.1 Mini | Llama 3.1 8B Instruct |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Meta
Llama 3.1 8B Instruct saves you $2.54/month
That's 96% cheaper than GPT-4.1 Mini 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-4.1 Mini | Llama 3.1 8B Instruct |
|---|---|---|
| Context Window | 1.0M | 16K |
| Max Output Tokens | 32,768 | 16,384 |
| Open Source | No | Yes |
| Created | Apr 14, 2025 | Jul 23, 2024 |
GPT-4.1 Mini scores 54/100 (rank #108) compared to Llama 3.1 8B Instruct's 52/100 (rank #110), giving it a 2-point advantage. GPT-4.1 Mini is the stronger overall choice, though Llama 3.1 8B Instruct may excel in specific areas like cost efficiency.
GPT-4.1 Mini is ranked #108 and Llama 3.1 8B Instruct is ranked #110 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.
Llama 3.1 8B Instruct is cheaper at $0.05/M output tokens vs GPT-4.1 Mini's $1.60/M output tokens - 32.0x more expensive. Input token pricing: GPT-4.1 Mini at $0.40/M vs Llama 3.1 8B Instruct at $0.02/M.
GPT-4.1 Mini has a larger context window of 1,047,576 tokens compared to Llama 3.1 8B Instruct's 16,384 tokens. A larger context window means the model can process longer documents and conversations.