| Signal | Claude Opus 4 | Delta | o3 Deep Research |
|---|---|---|---|
Capabilities | 83 | -17 | |
Benchmarks | 83 | -5 | |
Pricing | 75 | +35 | |
Context window size | 84 | -- | |
Recency | 77 | -23 | |
Output Capacity | 75 | -8 | |
| Overall Result | 1 wins | of 6 | 4 wins |
0
days ranked higher
0
days
30
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Anthropic
OpenAI
o3 Deep Research saves you $2250.00/month
That's $27000.00/year compared to Claude Opus 4 at your current usage level of 100K calls/month.
| Metric | Claude Opus 4 | o3 Deep Research | Winner |
|---|---|---|---|
| Overall Score | 82 | 92 | o3 Deep Research |
| Rank | #68 | #8 | o3 Deep Research |
| Quality Rank | #68 | #8 | o3 Deep Research |
| Adoption Rank | #68 | #8 | o3 Deep Research |
| Parameters | -- | -- | -- |
| Context Window | 200K | 200K | -- |
| Pricing | $15.00/$75.00/M | $10.00/$40.00/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 100 | o3 Deep Research |
| Benchmarks | 83 | 88 | o3 Deep Research |
| Pricing | 75 | 40 | Claude Opus 4 |
| Context window size | 84 | 84 | Claude Opus 4 |
| Recency | 77 | 100 | o3 Deep Research |
| Output Capacity | 75 | 83 | o3 Deep Research |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 82/100 (rank #68), placing it in the top 77% of all 290 models tracked.
Scores 92/100 (rank #8), placing it in the top 98% of all 290 models tracked.
o3 Deep Research has a 10-point advantage, which typically translates to noticeably better performance on complex reasoning, code generation, and multi-step tasks.
o3 Deep Research offers 44% better value per quality point. At 1M tokens/day, you'd spend $750.00/month with o3 Deep Research vs $1350.00/month with Claude Opus 4 - a $600.00 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. o3 Deep Research also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (200K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($40.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (92/100) 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
o3 Deep Research has a moderate advantage with a 9.900000000000006-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
o3 Deep Research
44% 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 | o3 Deep Research |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Anthropic
OpenAI
o3 Deep Research saves you $51.00/month
That's 44% 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 | o3 Deep Research |
|---|---|---|
| Context Window | 200K | 200K |
| Max Output Tokens | 32,000 | 100,000 |
| Open Source | No | No |
| Created | May 22, 2025 | Oct 10, 2025 |
o3 Deep Research scores 92/100 (rank #8) compared to Claude Opus 4's 82/100 (rank #68), giving it a 10-point advantage. o3 Deep Research is the stronger overall choice, though Claude Opus 4 may excel in specific areas like certain benchmarks.
Claude Opus 4 is ranked #68 and o3 Deep Research is ranked #8 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
o3 Deep Research is cheaper at $40.00/M output tokens vs Claude Opus 4's $75.00/M output tokens - 1.9x more expensive. Input token pricing: Claude Opus 4 at $15.00/M vs o3 Deep Research at $10.00/M.
Claude Opus 4 has a larger context window of 200,000 tokens compared to o3 Deep Research's 200,000 tokens. A larger context window means the model can process longer documents and conversations.