| Signal | Claude Opus 4 | Delta | GPT-5.3-Codex |
|---|---|---|---|
Capabilities | 83 | -17 | |
Benchmarks | 82 | -5 | |
Pricing | 25 | -61 | |
Context window size | 84 | -5 | |
Recency | 69 | -31 | |
Output Capacity | 75 | -10 | |
| Overall Result | 0 wins | of 6 | 6 wins |
Score History
82.1
current score
GPT-5.3-Codex
right now
88.7
current score
Anthropic
OpenAI
GPT-5.3-Codex saves you $4375.00/month
That's $52500.00/year compared to Claude Opus 4 at your current usage level of 100K calls/month.
| Metric | Claude Opus 4 | GPT-5.3-Codex | Winner |
|---|---|---|---|
| Overall Score | 82 | 89 | GPT-5.3-Codex |
| Rank | #31 | #9 | GPT-5.3-Codex |
| Quality Rank | #31 | #9 | GPT-5.3-Codex |
| Adoption Rank | #31 | #9 | GPT-5.3-Codex |
| Parameters | -- | -- | -- |
| Context Window | 200K | 400K | GPT-5.3-Codex |
| Pricing | $15.00/$75.00/M | $1.75/$14.00/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 100 | GPT-5.3-Codex |
| Benchmarks | 82 | 88 | GPT-5.3-Codex |
| Pricing | 25 | 86 | GPT-5.3-Codex |
| Context window size | 84 | 89 | GPT-5.3-Codex |
| Recency | 69 | 100 | GPT-5.3-Codex |
| Output Capacity | 75 | 85 | GPT-5.3-Codex |
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 #31), placing it in the top 90% 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 83% better value per quality point. At 1M tokens/day, you'd spend $236.25/month with GPT-5.3-Codex vs $1350.00/month with Claude Opus 4 - a $1113.75 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 (400K 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 6.6000000000000085-point lead in composite score. It wins on more signal dimensions, but Claude Opus 4 has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Claude Opus 4
Marginally better benchmark scores; both are excellent
Best for Cost
GPT-5.3-Codex
83% lower pricing; better value at scale
Best for Reliability
Claude Opus 4
Higher uptime and faster response speeds
Best for Prototyping
Claude Opus 4
Stronger community support and better developer experience
Best for Production
Claude Opus 4
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Opus 4 | GPT-5.3-Codex |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Anthropic
OpenAI
GPT-5.3-Codex saves you $97.05/month
That's 83% cheaper than Claude Opus 4 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 | GPT-5.3-Codex |
|---|---|---|
| Context Window | 200K | 400K |
| Max Output Tokens | 32,000 | 128,000 |
| Open Source | No | No |
| Created | May 22, 2025 | Feb 24, 2026 |