| Signal | GPT-5 Mini | Delta | Grok 4.1 Fast |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 64 | -12 | |
Pricing | 98 | -1 | |
Context window size | 89 | -11 | |
Recency | 83 | -17 | |
Output Capacity | 85 | +11 | |
| Overall Result | 1 wins | of 6 | 4 wins |
Score History
63.9
current score
Grok 4.1 Fast
right now
78
current score
OpenAI
xAI
Grok 4.1 Fast saves you $80.00/month
That's $960.00/year compared to GPT-5 Mini at your current usage level of 100K calls/month.
| Metric | GPT-5 Mini | Grok 4.1 Fast | Winner |
|---|---|---|---|
| Overall Score | 64 | 78 | Grok 4.1 Fast |
| Rank | #135 | #53 | Grok 4.1 Fast |
| Quality Rank | #135 | #53 | Grok 4.1 Fast |
| Adoption Rank | #135 | #53 | Grok 4.1 Fast |
| Parameters | -- | -- | -- |
| Context Window | 400K | 2000K | Grok 4.1 Fast |
| Pricing | $0.25/$2.00/M | $0.20/$0.50/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | GPT-5 Mini |
| Benchmarks | 64 | 76 | Grok 4.1 Fast |
| Pricing | 98 | 100 | Grok 4.1 Fast |
| Context window size | 89 | 100 | Grok 4.1 Fast |
| Recency | 83 | 100 | Grok 4.1 Fast |
| Output Capacity | 85 | 75 | GPT-5 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 64/100 (rank #135), placing it in the top 54% of all 290 models tracked.
Scores 78/100 (rank #53), placing it in the top 82% of all 290 models tracked.
Grok 4.1 Fast has a 14-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
Grok 4.1 Fast offers 69% better value per quality point. At 1M tokens/day, you'd spend $10.50/month with Grok 4.1 Fast vs $33.75/month with GPT-5 Mini - a $23.25 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. Grok 4.1 Fast also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (2000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.50/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (78/100) 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
Grok 4.1 Fast clearly outperforms GPT-5 Mini with a significant 14.100000000000001-point lead. For most general use cases, Grok 4.1 Fast is the stronger choice. However, GPT-5 Mini may still excel in niche scenarios.
Best for Quality
GPT-5 Mini
Marginally better benchmark scores; both are excellent
Best for Cost
Grok 4.1 Fast
69% lower pricing; better value at scale
Best for Reliability
GPT-5 Mini
Higher uptime and faster response speeds
Best for Prototyping
GPT-5 Mini
Stronger community support and better developer experience
Best for Production
GPT-5 Mini
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5 Mini | Grok 4.1 Fast |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
xAI
Grok 4.1 Fast saves you $1.89/month
That's 66% cheaper than GPT-5 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-5 Mini | Grok 4.1 Fast |
|---|---|---|
| Context Window | 400K | 2M |
| Max Output Tokens | 128,000 | 30,000 |
| Open Source | No | No |
| Created | Aug 7, 2025 | Nov 19, 2025 |
Grok 4.1 Fast's 75/100 score represents a 23% performance advantage over GPT-5 Mini's 61/100, suggesting the quality gap justifies the $2/M vs $0.5/M output pricing difference for production coding tasks. The 5x larger context window (2M vs 400K tokens) also enables Grok to handle entire codebases in a single prompt, making it more practical for large-scale refactoring despite the higher cost.
While GPT-5 Mini offers 4.3x more output tokens, its 14-point lower score (61 vs 75) and #14 ranking suggest the generated code quality may require more manual correction. For documentation generation or boilerplate code where volume matters more than optimization, GPT-5 Mini's $2/M output cost with 128K tokens could deliver better value than Grok's $0.5/M with only 30K tokens.
Grok 4.1 Fast's 2M token window can fit approximately 500K lines of code versus GPT-5 Mini's 100K lines, making Grok essential for analyzing entire monorepos or multiple microservices simultaneously. However, GPT-5 Mini's 400K tokens still exceed most single-file or module-level coding tasks, where its 20% cheaper input pricing ($0.25/M vs $0.20/M) becomes negligible compared to the 4x output cost difference.
Despite both supporting Vision, Function Calling, and Web Search, Grok 4.1 Fast's #1 ranking with 75/100 versus GPT-5 Mini's #14 with 61/100 likely stems from training data quality and model architecture rather than feature set. xAI's newer model architecture may better leverage the identical capability set, particularly for code understanding and generation tasks where the 23% performance delta becomes critical.
Migration makes sense for teams where code quality directly impacts revenue - Grok's 75/100 score justifies paying 4x more per output token ($0.5/M vs $2/M) if it reduces debugging time by even 25%. However, teams using GPT-5 Mini for high-volume, low-stakes code generation (test data, mocks, scaffolding) should stay put, as the $1.5/M output savings on a typical 10M token/month workload ($5K vs $20K) outweighs the 14-point performance difference.