OpenAI (67 models) vs Cohere (4 models) - compared across composite scores, pricing, capabilities, and context windows.
| OpenAI | Score | vs | Cohere | Score |
|---|---|---|---|---|
| GPT-5.4 Pro | 92 | Command A | 51 | |
| GPT-5.4 | 92 | Command R+ (08-2024) | 49 | |
| GPT-5.2 Pro | 91 | Command R7B (12-2024) | 36 |
| Capability | OpenAI | Cohere | Leader |
|---|---|---|---|
Vision | 45/67 | 0/4 | OpenAI |
Reasoning | 37/67 | 0/4 | OpenAI |
Function Calling | 57/67 | 2/4 | OpenAI |
JSON Mode | 63/67 | 4/4 | OpenAI |
Web Search | 28/67 | 0/4 | OpenAI |
Streaming | 65/67 | 4/4 | OpenAI |
Image Output | 4/67 | 0/4 | OpenAI |
| Metric | OpenAI | Cohere |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.030 gpt-oss-20b | $0.037 Command R7B (12-2024) |
| Cheapest Output (per 1M tokens) | $0.140 | $0.150 |
| Most Expensive Input (per 1M tokens) | $150.00 o1-pro | $2.50 Command A |
| Most Expensive Output (per 1M tokens) | $600.00 | $10.00 |
| Free Models | 2 | 0 |
| Max Context Window | 1.1M | 256K |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| GPT-5.4 Pro | 92 | $30.00 | $180.00 |
| GPT-5.4 | 92 | $2.50 | $15.00 |
| GPT-5.2 Pro | 91 | $21.00 | $168.00 |
| GPT-5.2-Codex | 90 | $1.75 | $14.00 |
| GPT-5.2 | 90 | $1.75 | $14.00 |
| GPT-5.3-Codex | 89 | $1.75 | $14.00 |
| GPT-5 Pro | 89 | $15.00 | $120.00 |
| GPT-5.1-Codex-Max | 88 | $1.25 | $10.00 |
| GPT-5 Codex | 88 | $1.25 | $10.00 |
| GPT-5 | 88 | $1.25 | $10.00 |
| GPT-5.3 Chat | 87 | $1.75 | $14.00 |
| GPT-5.1 | 87 | $1.25 | $10.00 |
| GPT-5.1-Codex | 87 | $1.25 | $10.00 |
| GPT-5.1-Codex-Mini | 87 | $0.250 | $2.00 |
| o3 Deep Research | 87 | $10.00 | $40.00 |
| o3 Pro | 87 | $20.00 | $80.00 |
| o3 | 87 | $2.00 | $8.00 |
| GPT-5.1 Chat | 87 | $1.25 | $10.00 |
| o4 Mini Deep Research | 81 | $2.00 | $8.00 |
| o4 Mini | 81 | $1.10 | $4.40 |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Command A | 51 | $2.50 | $10.00 |
| Command R+ (08-2024) | 49 | $2.50 | $10.00 |
| Command R (08-2024) | 49 | $0.150 | $0.600 |
| Command R7B (12-2024) | 36 | $0.037 | $0.150 |
Compare any two AI providers side-by-side.
OpenAI's 64-model portfolio reflects a fragmentation strategy with multiple versions, fine-tunes, and specialized models (42 with vision, 57 with function calling), while Cohere focuses on 4 general-purpose models with consistent capabilities. This means OpenAI users face more complex model selection decisions but get specialized options like GPT-5.4 (67/100 score) for specific tasks, whereas Cohere users get simpler deployments with Command R+ (38/100 score) handling most use cases at $10.00/M tokens output.
Cohere has 0 of 4 models supporting vision, making it unsuitable for any image analysis, document processing, or multimodal workflows, while OpenAI offers vision in 42 of 64 models (66%) including their top performers. This capability gap means teams needing OCR, visual QA, or image-to-text must use OpenAI despite Cohere's competitive text performance at 36/100 average score versus OpenAI's 49/100.
OpenAI's pricing spans from commodity models at $0.110/M tokens to specialized high-compute models at $600/M, reflecting everything from basic chat to advanced reasoning systems across their 64-model range. Cohere's narrower $0.150-$10.00/M range across just 4 models suggests a focus on production text generation without the extreme ends of OpenAI's portfolio, though their cheapest option still costs 36% more than OpenAI's entry point.
Despite OpenAI's 5 open source models representing only 8% of their 64-model portfolio, they still provide more self-hosting options than Cohere's single open model (25% of their 4 total). However, neither provider truly prioritizes on-premise deployment compared to API-first operations, with OpenAI's top performer GPT-5.4 (67/100) and Cohere's Command R+ (38/100) both remaining closed source.
OpenAI's 1.1M token context window enables processing entire codebases or book-length documents in a single call, while Cohere's 256K limit requires chunking strategies for large inputs despite still exceeding most practical needs. This 4.3x context advantage matters most for specialized use cases like repository-wide code analysis or legal document review, though both far exceed typical conversation needs where Cohere's lower pricing ($0.150/M minimum) might offset the limitation.
Cohere's Command R+ (38/100) targets production deployments requiring consistent performance and SLAs at $10.00/M tokens, while OpenAI's 2 free models likely have usage limits, rate restrictions, or no enterprise support despite potentially higher scores. The choice reflects a build-vs-buy decision where Cohere users pay for reliability and simplicity across their 4-model lineup versus navigating OpenAI's complex 64-model ecosystem with varying availability tiers.