| Signal | Command R (08-2024) | Delta | GPT-4 Turbo (older v1106) |
|---|---|---|---|
Capabilities | 50 | -- | |
Benchmarks | 47 | +47 | |
Pricing | 1 | -29 | |
Context window size | 81 | -- | |
Recency | 29 | +29 | |
Output Capacity | 60 | 0 | |
| Overall Result | 2 wins | of 6 | 2 wins |
27
days ranked higher
2
days
1
days ranked higher
Cohere
OpenAI
Command R (08-2024) saves you $2455.00/month
That's $29460.00/year compared to GPT-4 Turbo (older v1106) at your current usage level of 100K calls/month.
| Metric | Command R (08-2024) | GPT-4 Turbo (older v1106) | Winner |
|---|---|---|---|
| Overall Score | 48 | 43 | Command R (08-2024) |
| Rank | #264 | #278 | Command R (08-2024) |
| Quality Rank | #264 | #278 | Command R (08-2024) |
| Adoption Rank | #264 | #278 | Command R (08-2024) |
| Parameters | -- | -- | -- |
| Context Window | 128K | 128K | -- |
| Pricing | $0.15/$0.60/M | $10.00/$30.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Command R (08-2024) |
| Benchmarks | 47 | -- | Command R (08-2024) |
| Pricing | 1 | 30 | GPT-4 Turbo (older v1106) |
| Context window size | 81 | 81 | Command R (08-2024) |
| Recency | 29 | 0 | Command R (08-2024) |
| Output Capacity | 60 | 60 | GPT-4 Turbo (older v1106) |
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 48/100 (rank #264), placing it in the top 9% of all 290 models tracked.
Scores 43/100 (rank #278), placing it in the top 4% of all 290 models tracked.
With only a 5-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Command R (08-2024) offers 98% better value per quality point. At 1M tokens/day, you'd spend $11.25/month with Command R (08-2024) vs $600.00/month with GPT-4 Turbo (older v1106) - a $588.75 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
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. Command R (08-2024) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.60/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (48/100) correlates with better nuance, coherence, and style in long-form content
Command R (08-2024) has a moderate advantage with a 4.899999999999999-point lead in composite score. It wins on more signal dimensions, but GPT-4 Turbo (older v1106) has specific strengths that could make it the better choice for certain workflows.
Best for Quality
Command R (08-2024)
Marginally better benchmark scores; both are excellent
Best for Cost
Command R (08-2024)
98% lower pricing; better value at scale
Best for Reliability
Command R (08-2024)
Higher uptime and faster response speeds
Best for Prototyping
Command R (08-2024)
Stronger community support and better developer experience
Best for Production
Command R (08-2024)
Wider enterprise adoption and proven at scale
by Cohere
| Capability | Command R (08-2024) | GPT-4 Turbo (older v1106) |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Cohere
OpenAI
Command R (08-2024) saves you $53.01/month
That's 98% cheaper than GPT-4 Turbo (older v1106) 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 | Command R (08-2024) | GPT-4 Turbo (older v1106) |
|---|---|---|
| Context Window | 128K | 128K |
| Max Output Tokens | 4,000 | 4,096 |
| Open Source | No | No |
| Created | Aug 30, 2024 | Nov 6, 2023 |
Command R (08-2024) scores 48/100 (rank #264) compared to GPT-4 Turbo (older v1106)'s 43/100 (rank #278), giving it a 5-point advantage. Command R (08-2024) is the stronger overall choice, though GPT-4 Turbo (older v1106) may excel in specific areas like certain benchmarks.
Command R (08-2024) is ranked #264 and GPT-4 Turbo (older v1106) is ranked #278 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.
Command R (08-2024) is cheaper at $0.60/M output tokens vs GPT-4 Turbo (older v1106)'s $30.00/M output tokens - 50.0x more expensive. Input token pricing: Command R (08-2024) at $0.15/M vs GPT-4 Turbo (older v1106) at $10.00/M.
Command R (08-2024) has a larger context window of 128,000 tokens compared to GPT-4 Turbo (older v1106)'s 128,000 tokens. A larger context window means the model can process longer documents and conversations.