| Signal | Command R7B (12-2024) | Delta | GLM 4 32B |
|---|---|---|---|
Capabilities | 33 | -- | |
Benchmarks | 38 | -6 | |
Pricing | 100 | -- | |
Context window size | 73 | -- | |
Recency | 37 | -40 | |
Output Capacity | 60 | +40 | |
| Overall Result | 1 wins | of 6 | 2 wins |
Score History
35.4
current score
Command R7B (12-2024)
right now
35.2
current score
Cohere
Zhipu AI
Command R7B (12-2024) saves you $3.75/month
That's $45.00/year compared to GLM 4 32B at your current usage level of 100K calls/month.
| Metric | Command R7B (12-2024) | GLM 4 32B | Winner |
|---|---|---|---|
| Overall Score | 35 | 35 | Command R7B (12-2024) |
| Rank | #317 | #319 | Command R7B (12-2024) |
| Quality Rank | #317 | #319 | Command R7B (12-2024) |
| Adoption Rank | #317 | #319 | Command R7B (12-2024) |
| Parameters | 7B | 32B | -- |
| Context Window | 128K | 128K | -- |
| Pricing | $0.04/$0.15/M | $0.10/$0.10/M | -- |
| Signal Scores | |||
| Capabilities | 33 | 33 | Command R7B (12-2024) |
| Benchmarks | 38 | 44 | GLM 4 32B |
| Pricing | 100 | 100 | Command R7B (12-2024) |
| Context window size | 73 | 73 | Command R7B (12-2024) |
| Recency | 37 | 77 | GLM 4 32B |
| Output Capacity | 60 | 20 | Command R7B (12-2024) |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 35/100 (rank #317), placing it in the top -9% of all 290 models tracked.
Scores 35/100 (rank #319), placing it in the top -10% of all 290 models tracked.
With only a 0-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 R7B (12-2024) offers 6% better value per quality point. At 1M tokens/day, you'd spend $2.81/month with Command R7B (12-2024) vs $3.00/month with GLM 4 32B - a $0.19 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
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. GLM 4 32B 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 ($0.10/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (35/100) correlates with better nuance, coherence, and style in long-form content
Command R7B (12-2024) and GLM 4 32B are extremely close in overall performance (only 0.19999999999999574 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Command R7B (12-2024)
Marginally better benchmark scores; both are excellent
Best for Cost
Command R7B (12-2024)
6% lower pricing; better value at scale
Best for Reliability
Command R7B (12-2024)
Higher uptime and faster response speeds
Best for Prototyping
Command R7B (12-2024)
Stronger community support and better developer experience
Best for Production
Command R7B (12-2024)
Wider enterprise adoption and proven at scale
by Cohere
| Capability | Command R7B (12-2024) | GLM 4 32B |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Cohere
Zhipu AI
Command R7B (12-2024) saves you $0.0525/month
That's 17% cheaper than GLM 4 32B 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 R7B (12-2024) | GLM 4 32B |
|---|---|---|
| Context Window | 128K | 128K |
| Max Output Tokens | 4,000 | -- |
| Open Source | No | No |
| Created | Dec 14, 2024 | Jul 24, 2025 |