| Signal | Claude Opus 4.6 (Fast) | Delta | GPT-5.4 Mini |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 87 | -3 | |
Pricing | 5 | -90 | |
Context window size | 86 | +6 | |
Recency | 100 | -- | |
Output Capacity | 85 | -- | |
| Overall Result | 1 wins | of 6 | 2 wins |
Score History
90
current score
Claude Opus 4.6 (Fast)
right now
78.8
current score
Anthropic
OpenAI
GPT-5.4 Mini saves you $10200.00/month
That's $122400.00/year compared to Claude Opus 4.6 (Fast) at your current usage level of 100K calls/month.
| Metric | Claude Opus 4.6 (Fast) | GPT-5.4 Mini | Winner |
|---|---|---|---|
| Overall Score | 90 | 79 | Claude Opus 4.6 (Fast) |
| Rank | #12 | #47 | Claude Opus 4.6 (Fast) |
| Quality Rank | #12 | #47 | Claude Opus 4.6 (Fast) |
| Adoption Rank | #12 | #47 | Claude Opus 4.6 (Fast) |
| Parameters | -- | -- | -- |
| Context Window | 1000K | 400K | Claude Opus 4.6 (Fast) |
| Pricing | $30.00/$150.00/M | $0.75/$4.50/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | Claude Opus 4.6 (Fast) |
| Benchmarks | 87 | 90 | GPT-5.4 Mini |
| Pricing | 5 | 96 | GPT-5.4 Mini |
| Context window size | 86 | 80 | Claude Opus 4.6 (Fast) |
| Recency | 100 | 100 | Claude Opus 4.6 (Fast) |
| Output Capacity | 85 | 85 | Claude Opus 4.6 (Fast) |
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 90/100 (rank #12), placing it in the top 96% of all 290 models tracked.
Scores 79/100 (rank #47), placing it in the top 84% of all 290 models tracked.
Claude Opus 4.6 (Fast) has a 11-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
GPT-5.4 Mini offers 97% better value per quality point. At 1M tokens/day, you'd spend $78.75/month with GPT-5.4 Mini vs $2700.00/month with Claude Opus 4.6 (Fast) - a $2621.25 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. GPT-5.4 Mini also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($4.50/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (90/100) 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
Claude Opus 4.6 (Fast) clearly outperforms GPT-5.4 Mini with a significant 11.200000000000003-point lead. For most general use cases, Claude Opus 4.6 (Fast) is the stronger choice. However, GPT-5.4 Mini may still excel in niche scenarios.
Best for Quality
Claude Opus 4.6 (Fast)
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5.4 Mini
97% lower pricing; better value at scale
Best for Reliability
Claude Opus 4.6 (Fast)
Higher uptime and faster response speeds
Best for Prototyping
Claude Opus 4.6 (Fast)
Stronger community support and better developer experience
Best for Production
Claude Opus 4.6 (Fast)
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Opus 4.6 (Fast) | GPT-5.4 Mini |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Anthropic
OpenAI
GPT-5.4 Mini saves you $227.25/month
That's 97% cheaper than Claude Opus 4.6 (Fast) 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 | Claude Opus 4.6 (Fast) | GPT-5.4 Mini |
|---|---|---|
| Context Window | 1M | 400K |
| Max Output Tokens | 128,000 | 128,000 |
| Open Source | No | No |
| Created | Apr 7, 2026 | Mar 17, 2026 |
For high-volume production workloads, absolutely not - GPT-5.4 Mini at $4.5/M output tokens delivers 98.4% of Claude's performance at 3% of the cost. However, Claude's 2.5x larger context window (1M vs 400K tokens) justifies the premium for specialized use cases like analyzing entire codebases or processing long technical documentation where context overflow would force multiple GPT-5.4 Mini calls.
The 62/100 score reflects raw coding performance where Claude edges out GPT-5.4 Mini by just 1.6%, but the ranking also factors in the 1M token context window which enables single-shot analysis of 25,000+ line codebases. At $30/M input tokens, Claude is actually competitive for read-heavy operations like code review and documentation generation where the output-to-input ratio stays below 5:1.
Claude's 1M token window becomes essential for monorepo analysis, multi-file refactoring, or maintaining context across 50+ file changes - scenarios where GPT-5.4 Mini's 400K limit would require context pruning. The $150/M output cost becomes acceptable when amortized across enterprise teams needing guaranteed context retention for complex architectural decisions or compliance-critical code reviews.
For a typical coding session with 100K input tokens and 10K output tokens, GPT-5.4 Mini costs $0.12 versus Claude's $4.50 - a 37.5x difference. This makes GPT-5.4 Mini the clear choice for continuous coding assistance, while Claude becomes cost-effective only for specific high-context tasks where its 2.5x larger window prevents the need for multiple model calls.
Despite the metadata difference, both models handle code files through their text interfaces, achieving 62 and 61 scores respectively in coding benchmarks. The real differentiator is context utilization: Claude can process 250 typical source files (4K tokens each) simultaneously versus GPT-5.4 Mini's 100 files, making the 33.3x output price premium worthwhile only for large-scale codebase operations.