| Signal | Claude Sonnet 4.6 | Delta | GPT-5 Image Mini |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 82 | -5 | |
Pricing | 85 | -13 | |
Context window size | 95 | -5 | |
Recency | 100 | +5 | |
Output Capacity | 85 | -15 | |
| Overall Result | 1 wins | of 6 | 4 wins |
Score History
85.2
current score
GPT-5 Image Mini
right now
89.2
current score
Anthropic
OpenAI
GPT-5 Image Mini saves you $700.00/month
That's $8400.00/year compared to Claude Sonnet 4.6 at your current usage level of 100K calls/month.
| Metric | Claude Sonnet 4.6 | GPT-5 Image Mini | Winner |
|---|---|---|---|
| Overall Score | 85 | 89 | GPT-5 Image Mini |
| Rank | #25 | #2 | GPT-5 Image Mini |
| Quality Rank | #25 | #2 | GPT-5 Image Mini |
| Adoption Rank | #25 | #2 | GPT-5 Image Mini |
| Parameters | -- | -- | -- |
| Context Window | 1000K | 400K | Claude Sonnet 4.6 |
| Pricing | $3.00/$15.00/M | $2.50/$2.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | Claude Sonnet 4.6 |
| Benchmarks | 82 | 88 | GPT-5 Image Mini |
| Pricing | 85 | 98 | GPT-5 Image Mini |
| Context window size | 95 | 100 | GPT-5 Image Mini |
| Recency | 100 | 95 | Claude Sonnet 4.6 |
| Output Capacity | 85 | 100 | GPT-5 Image 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 85/100 (rank #25), placing it in the top 92% of all 290 models tracked.
Scores 89/100 (rank #2), placing it in the top 100% of all 290 models tracked.
With only a 4-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 Image Mini offers 75% better value per quality point. At 1M tokens/day, you'd spend $67.50/month with GPT-5 Image Mini vs $270.00/month with Claude Sonnet 4.6 - a $202.50 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 Image 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 ($2.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (89/100) 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-5 Image Mini has a moderate advantage with a 4-point lead in composite score. It wins on more signal dimensions, but Claude Sonnet 4.6 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Claude Sonnet 4.6
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5 Image Mini
75% lower pricing; better value at scale
Best for Reliability
Claude Sonnet 4.6
Higher uptime and faster response speeds
Best for Prototyping
Claude Sonnet 4.6
Stronger community support and better developer experience
Best for Production
Claude Sonnet 4.6
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Sonnet 4.6 | GPT-5 Image Mini |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Outputdiffers |
Anthropic
OpenAI
GPT-5 Image Mini saves you $16.50/month
That's 71% cheaper than Claude Sonnet 4.6 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 4.6 | GPT-5 Image Mini |
|---|---|---|
| Context Window | 1M | 400K |
| Max Output Tokens | 128,000 | 128,000 |
| Open Source | No | No |
| Created | Feb 17, 2026 | Oct 16, 2025 |
GPT-5 Image Mini's 0/100 score and #0 rank indicate it's either a preview release or lacks sufficient benchmark data, despite having competitive pricing at $2.5/M input and $2/M output. The model's inclusion of image generation capabilities alongside its 400K token context window suggests OpenAI is testing a multimodal architecture that trades proven performance for broader functionality.
For coding-specific tasks, Claude Sonnet 4.6's $15/M output cost delivers proven performance (66/100 score, #6 rank) and a 2.5x larger context window at 1M tokens. GPT-5 Image Mini's unproven 0/100 score makes it a risky choice for production code generation, though its $2/M output pricing and image generation capability could make sense for experimental multimodal applications.
Claude Sonnet 4.6's 1M token context allows processing entire mid-size repositories or multiple related files simultaneously, compared to GPT-5 Image Mini's 400K limit. This 2.5x advantage translates to analyzing roughly 750,000 more characters of code per request, critical for refactoring tasks or understanding complex dependencies across files.
GPT-5 Image Mini's text+image output modality at $2/M output offers an integrated solution, but its 0/100 score suggests waiting for proven benchmarks. Splitting workloads between Claude Sonnet 4.6 (66/100 score for code) and a specialized image generator would cost more at $15/M output for text but delivers production-ready performance today.
This inverted pricing (1.25x input/output ratio) compared to Claude Sonnet 4.6's traditional structure ($3/M input, $15/M output) suggests GPT-5 Image Mini optimizes for image generation workflows where input processing is computationally expensive. The model's file input capability and 400K context window indicate it's designed for document-to-image or code-to-diagram transformations rather than pure text generation.