DeepSeek (13 models) vs Cohere (4 models) - compared across composite scores, pricing, capabilities, and context windows.
| DeepSeek | Score | vs | Cohere | Score |
|---|---|---|---|---|
| R1 0528 | 79 | Command A | 51 | |
| DeepSeek V4 Pro | 76 | Command R+ (08-2024) | 49 | |
| R1 | 73 | Command R7B (12-2024) | 36 |
| Capability | DeepSeek | Cohere | Leader |
|---|---|---|---|
Vision | 0/13 | 0/4 | Tie |
Reasoning | 11/13 | 0/4 | DeepSeek |
Function Calling | 10/13 | 2/4 | DeepSeek |
JSON Mode | 12/13 | 4/4 | DeepSeek |
Web Search | 0/13 | 0/4 | Tie |
Streaming | 13/13 | 4/4 | DeepSeek |
Image Output | 0/13 | 0/4 | Tie |
| Metric | DeepSeek | Cohere |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.140 DeepSeek V4 Flash | $0.037 Command R7B (12-2024) |
| Cheapest Output (per 1M tokens) | $0.280 | $0.150 |
| Most Expensive Input (per 1M tokens) | $0.700 R1 | $2.50 Command A |
| Most Expensive Output (per 1M tokens) | $2.50 | $10.00 |
| Free Models | 0 | 0 |
| Max Context Window | 1.0M | 256K |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| R1 0528 | 79 | $0.500 | $2.15 |
| DeepSeek V4 Pro | 76 | $0.435 | $0.870 |
| R1 | 73 | $0.700 | $2.50 |
| DeepSeek V4 Flash | 72 | $0.140 | $0.280 |
| DeepSeek V3 0324 | 72 | $0.200 | $0.770 |
| DeepSeek V3.2 | 70 | $0.252 | $0.378 |
| DeepSeek V3.2 Exp | 70 | $0.270 | $0.410 |
| DeepSeek V3 | 70 | $0.320 | $0.890 |
| DeepSeek V3.1 Terminus | 69 | $0.270 | $0.950 |
| DeepSeek V3.1 | 69 | $0.150 | $0.750 |
| R1 Distill Llama 70B | 42 | $0.700 | $0.800 |
| DeepSeek V3.2 Speciale | 40 | $0.287 | $0.431 |
| R1 Distill Qwen 32B | 37 | $0.290 | $0.290 |
| 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.
DeepSeek's portfolio strategy emphasizes open source diversity with 11 models spanning $0.290-$2.50/M tokens, achieving modest performance across the board with their top model (DeepSeek V3.2 Exp) hitting 46/100. Cohere takes a concentrated approach with 4 models, accepting lower average scores (36/100) while offering the market's lowest entry price at $0.150/M tokens for basic tasks.
DeepSeek has invested heavily in reasoning capabilities across 91% of their portfolio, likely targeting code generation and analytical workloads where their 164K context window suffices. Cohere's complete absence of reasoning support across all 4 models suggests they're optimizing for different use cases like retrieval and generation tasks that benefit from their larger 256K context window.
Cohere's aggressive $0.150/M entry price (48% cheaper than DeepSeek's minimum) targets high-volume, cost-sensitive applications despite trailing performance by 8 points at the top end. DeepSeek's narrower price range ($0.290-$2.50/M) across 11 models suggests they're betting on performance consistency over price competition, with most models clustered in the mid-tier pricing band.
Cohere's Command R+ offers 256K context (56% more than DeepSeek's 164K maximum) at competitive rates, making it superior for long-document processing despite the 8-point performance gap. Additionally, with only 1 open source model versus DeepSeek's full open source portfolio of 11, Cohere users get enterprise support and SLAs that self-hosted DeepSeek deployments lack.
DeepSeek's 73% function calling coverage across models makes them ideal for agent-based systems and tool-using applications, especially combined with their reasoning capabilities on 10/11 models. Cohere's 50% function calling support limits them to simpler integration scenarios, though their superior 256K context window better serves RAG applications where function calls primarily handle retrieval rather than complex tool orchestration.