| Signal | Claude Sonnet 4.5 | Delta | GPT-5.4 Mini |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 82 | -8 | |
Pricing | 85 | -10 | |
Context window size | 95 | +6 | |
Recency | 92 | -8 | |
Output Capacity | 80 | -5 | |
| Overall Result | 1 wins | of 6 | 4 wins |
Score History
82.4
current score
Claude Sonnet 4.5
right now
79.3
current score
Anthropic
OpenAI
GPT-5.4 Mini saves you $750.00/month
That's $9000.00/year compared to Claude Sonnet 4.5 at your current usage level of 100K calls/month.
| Metric | Claude Sonnet 4.5 | GPT-5.4 Mini | Winner |
|---|---|---|---|
| Overall Score | 82 | 79 | Claude Sonnet 4.5 |
| Rank | #30 | #43 | Claude Sonnet 4.5 |
| Quality Rank | #30 | #43 | Claude Sonnet 4.5 |
| Adoption Rank | #30 | #43 | Claude Sonnet 4.5 |
| Parameters | -- | -- | -- |
| Context Window | 1000K | 400K | Claude Sonnet 4.5 |
| Pricing | $3.00/$15.00/M | $0.75/$4.50/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | Claude Sonnet 4.5 |
| Benchmarks | 82 | 90 | GPT-5.4 Mini |
| Pricing | 85 | 96 | GPT-5.4 Mini |
| Context window size | 95 | 89 | Claude Sonnet 4.5 |
| Recency | 92 | 100 | GPT-5.4 Mini |
| Output Capacity | 80 | 85 | GPT-5.4 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 82/100 (rank #30), placing it in the top 90% of all 290 models tracked.
Scores 79/100 (rank #43), placing it in the top 86% 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.
GPT-5.4 Mini offers 71% better value per quality point. At 1M tokens/day, you'd spend $78.75/month with GPT-5.4 Mini vs $270.00/month with Claude Sonnet 4.5 - a $191.25 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 (82/100) 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 Sonnet 4.5 has a moderate advantage with a 3.1000000000000085-point lead in composite score. It wins on more signal dimensions, but GPT-5.4 Mini has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Claude Sonnet 4.5
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5.4 Mini
71% lower pricing; better value at scale
Best for Reliability
Claude Sonnet 4.5
Higher uptime and faster response speeds
Best for Prototyping
Claude Sonnet 4.5
Stronger community support and better developer experience
Best for Production
Claude Sonnet 4.5
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Sonnet 4.5 | 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 $16.65/month
That's 71% cheaper than Claude Sonnet 4.5 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 Sonnet 4.5 | GPT-5.4 Mini |
|---|---|---|
| Context Window | 1M | 400K |
| Max Output Tokens | 64,000 | 128,000 |
| Open Source | No | No |
| Created | Sep 29, 2025 | Mar 17, 2026 |
For high-volume code generation tasks, GPT-5.4 Mini's $4.5/M output pricing delivers 94% of Claude's performance at 30% of the cost. However, Claude's 2.5x larger context window (1M vs 400K tokens) becomes critical for complex refactoring jobs where you need to analyze entire codebases - making the $15/M output cost justifiable for enterprise-scale migrations where the 4-point quality gap could mean fewer debugging cycles.
OpenAI appears to have optimized GPT-5.4 Mini for bulk code generation use cases where quantity matters - think generating extensive test suites or documentation. The 61/100 score suggests it produces slightly more verbose or less optimized code than Claude's 65/100, but at $0.75/M input (vs Claude's $3/M), it's architected for teams prioritizing throughput over perfection.
Despite feature parity on paper, Claude's #8 ranking vs GPT-5.4 Mini's #15 suggests superior training data curation or architectural choices specifically for code understanding. The 4-point score gap likely manifests in better handling of edge cases, more idiomatic code generation, and fewer syntax errors - worth the 3.3x output premium for teams where developer time reviewing AI-generated code exceeds API costs.
Monthly costs would be $66 for GPT-5.4 Mini (7M × $0.75/M + 3M × $4.5/M) versus $66 for Claude (7M × $3/M + 3M × $15/M) - a 3.2x difference or $150/month. For context-heavy applications leveraging Claude's 1M token window, you're essentially paying $84 extra monthly for a 6.6% performance improvement and 2.5x larger working memory.
Migration only makes sense for specific workloads: Claude's 1M context window enables processing 2.5x larger codebases in single passes, and its 65-point score suggests measurably better code quality. However, if your pipeline depends on GPT-5.4 Mini's 128K max output for generating large artifacts, Claude's 64K limit requires architectural changes that may offset the 4-point quality gain.