| Signal | Claude Opus 4.7 | Delta | GPT-5.3-Codex |
|---|---|---|---|
Capabilities | 100 | -- | |
Benchmarks | 80 | -8 | |
Pricing | 75 | -11 | |
Context window size | 95 | +6 | |
Recency | 100 | -- | |
Output Capacity | 85 | -- | |
| Overall Result | 1 wins | of 6 | 2 wins |
Score History
81.4
current score
GPT-5.3-Codex
right now
88.7
current score
Anthropic
OpenAI
GPT-5.3-Codex saves you $875.00/month
That's $10500.00/year compared to Claude Opus 4.7 at your current usage level of 100K calls/month.
| Metric | Claude Opus 4.7 | GPT-5.3-Codex | Winner |
|---|---|---|---|
| Overall Score | 81 | 89 | GPT-5.3-Codex |
| Rank | #32 | #9 | GPT-5.3-Codex |
| Quality Rank | #32 | #9 | GPT-5.3-Codex |
| Adoption Rank | #32 | #9 | GPT-5.3-Codex |
| Parameters | -- | -- | -- |
| Context Window | 1000K | 400K | Claude Opus 4.7 |
| Pricing | $5.00/$25.00/M | $1.75/$14.00/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 100 | Claude Opus 4.7 |
| Benchmarks | 80 | 88 | GPT-5.3-Codex |
| Pricing | 75 | 86 | GPT-5.3-Codex |
| Context window size | 95 | 89 | Claude Opus 4.7 |
| Recency | 100 | 100 | Claude Opus 4.7 |
| Output Capacity | 85 | 85 | Claude Opus 4.7 |
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 81/100 (rank #32), placing it in the top 89% of all 290 models tracked.
Scores 89/100 (rank #9), placing it in the top 97% of all 290 models tracked.
GPT-5.3-Codex has a 7-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
GPT-5.3-Codex offers 48% better value per quality point. At 1M tokens/day, you'd spend $236.25/month with GPT-5.3-Codex vs $450.00/month with Claude Opus 4.7 - a $213.75 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-5.3-Codex 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 ($14.00/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-5.3-Codex has a moderate advantage with a 7.299999999999997-point lead in composite score. It wins on more signal dimensions, but Claude Opus 4.7 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Claude Opus 4.7
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5.3-Codex
48% lower pricing; better value at scale
Best for Reliability
Claude Opus 4.7
Higher uptime and faster response speeds
Best for Prototyping
Claude Opus 4.7
Stronger community support and better developer experience
Best for Production
Claude Opus 4.7
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Opus 4.7 | GPT-5.3-Codex |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Anthropic
OpenAI
GPT-5.3-Codex saves you $19.05/month
That's 49% cheaper than Claude Opus 4.7 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 4.7 | GPT-5.3-Codex |
|---|---|---|
| Context Window | 1M | 400K |
| Max Output Tokens | 128,000 | 128,000 |
| Open Source | No | No |
| Created | Apr 16, 2026 | Feb 24, 2026 |