Cohere (4 models) vs Microsoft (3 models) - compared across composite scores, pricing, capabilities, and context windows.
| Cohere | Score | vs | Microsoft | Score |
|---|---|---|---|---|
| Command A | 51 | Phi 4 Mini Instruct | 53 | |
| Command R+ (08-2024) | 49 | Phi 4 | 60 | |
| Command R (08-2024) | 49 | WizardLM-2 8x22B | 28 |
| Capability | Cohere | Microsoft | Leader |
|---|---|---|---|
Vision | 0/4 | 0/3 | Tie |
Reasoning | 0/4 | 0/3 | Tie |
Function Calling | 2/4 | 0/3 | Cohere |
JSON Mode | 4/4 | 2/3 | Cohere |
Web Search | 0/4 | 0/3 | Tie |
Streaming | 4/4 | 3/3 | Cohere |
Image Output | 0/4 | 0/3 | Tie |
| Metric | Cohere | Microsoft |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.037 Command R7B (12-2024) | $0.065 Phi 4 |
| Cheapest Output (per 1M tokens) | $0.150 | $0.140 |
| Most Expensive Input (per 1M tokens) | $2.50 Command A | $0.620 WizardLM-2 8x22B |
| Most Expensive Output (per 1M tokens) | $10.00 | $0.620 |
| Free Models | 0 | 0 |
| Max Context Window | 256K | 128K |
| 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 |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Phi 4 | 60 | $0.065 | $0.140 |
| Phi 4 Mini Instruct | 53 | $0.080 | $0.350 |
| WizardLM-2 8x22B | 28 | $0.620 | $0.620 |
Compare any two AI providers side-by-side.
Cohere's Command R+ costs $10.00/M tokens output versus Phi 4's $0.620/M tokens, making it 16x more expensive for just 6 points better performance. The premium appears unjustified given that Command R+ lacks vision and reasoning capabilities (0/4 on both) while only offering function calling (2/4 models) as its distinguishing feature.
Microsoft open sources 100% of its models while Cohere keeps 75% proprietary, yet Microsoft achieves competitive pricing at $0.140-$0.620/M tokens versus Cohere's $0.150-$10.00/M range. This suggests Microsoft prioritizes ecosystem adoption over direct monetization, while Cohere bets on premium pricing for proprietary technology despite lower overall scores (36/100 average vs 29/100).
Cohere supports up to 256K context tokens versus Microsoft's 66K maximum, giving Cohere nearly 4x the context capacity. However, accessing Cohere's large context models costs significantly more, with their cheapest option at $0.150/M tokens compared to Microsoft's $0.140/M tokens, making Microsoft more cost-effective for applications that fit within 66K tokens.
Both Cohere (0/4 vision, 0/4 reasoning) and Microsoft (0/2 vision, 0/2 reasoning) have zero models supporting these increasingly critical capabilities. This positions both providers poorly for multimodal applications, with Cohere's only differentiator being function calling support in 2 of 4 models versus Microsoft's complete absence of advanced features across both models.
Cohere's extreme price range ($0.150 to $10.00/M tokens) suggests a segmented strategy targeting both budget and enterprise customers with distinct model tiers. Microsoft's narrower range ($0.140 to $0.620/M tokens) indicates a more focused approach on the low-to-mid market, consistent with their open source strategy and lower average model scores (29/100 vs 36/100).