Model comparison
Gemini 2.0 Flash-Lite vs Command R7B (12-2024)
- Input
- $0.075 per 1M tokens
- Output
- $0.30 per 1M tokens
- Context
- 1,048,576 tokens (1M)
- Released
- 2025-02-01
- Input
- $0.0375 / 1M tokens
- Output
- $0.15 / 1M tokens
- Context
- 128K
- Released
- 2024-12-13
Gemini 2.0 Flash-Lite scores higher on 2 of the 2 benchmarks both models report; Command R7B (12-2024) is cheaper on input tokens ($0 vs $0.1 per 1M, 2×); Gemini 2.0 Flash-Lite has the larger context window (1.048576M vs 128K); Command R7B (12-2024) ships open weights while Gemini 2.0 Flash-Lite is API-only.
Specs and pricing side by side
| Spec | Gemini 2.0 Flash-Lite | Command R7B (12-2024) |
|---|---|---|
| Maker | Cohere | |
| Released | 2025-02-01 | 2024-12-13 |
| Context window | 1,048,576 tokens (1M) | 128K |
| Max output | 8,192 tokens | 4K |
| Input price | $0.075 per 1M tokens | $0.0375 / 1M tokens |
| Output price | $0.30 per 1M tokens | $0.15 / 1M tokens |
| Parameters | not published | 7B |
| License | Proprietary | CC-BY-NC 4.0 (open weights, non-commercial; commercial use via Cohere API) |
| Weights | API only | Open weights |
| Modalities | Text, Image, Audio, Video | Text |
| Knowledge cutoff | June 2024 | not published |
Benchmarks both models report
| Benchmark | Gemini 2.0 Flash-Lite | Command R7B (12-2024) |
|---|---|---|
| MMLU-Pro | 71.6% | 28.5% |
| MATH | 86.8% | 26.4% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Gemini 2.0 Flash-Lite if…
- You care about MMLU-Pro, MATH (it scores higher on 2 shared benchmarks).
- You need the longer context (1.048576M vs 128K).
- You need Image / Audio / Video input, which Command R7B (12-2024) lacks.
- Your use case is: high-volume text generation such as captioning, tagging, and summarization at scale.
Pick Command R7B (12-2024) if…
- Cost matters: input tokens cost 2× less ($0 vs $0.1 per 1M).
- You want to self-host or fine-tune (open weights, CC-BY-NC 4.0 (open weights, non-commercial; commercial use via Cohere API)).
- Your use case is: high-volume, latency-sensitive RAG over long documents and knowledge bases.
FAQ
Which is better, Gemini 2.0 Flash-Lite or Command R7B (12-2024)?
Gemini 2.0 Flash-Lite scores higher on 2 of the 2 benchmarks both models report; Command R7B (12-2024) is cheaper on input tokens ($0 vs $0.1 per 1M, 2×); Gemini 2.0 Flash-Lite has the larger context window (1.048576M vs 128K); Command R7B (12-2024) ships open weights while Gemini 2.0 Flash-Lite is API-only. The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Command R7B (12-2024)?
Gemini 2.0 Flash-Lite: $0.075 per 1M tokens input, $0.30 per 1M tokens output. Command R7B (12-2024): $0.0375 / 1M tokens input, $0.15 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Gemini 2.0 Flash-Lite and Command R7B (12-2024)?
Gemini 2.0 Flash-Lite offers 1,048,576 tokens (1M) with up to 8,192 tokens output; Command R7B (12-2024) offers 128K with up to 4K output.
Is Gemini 2.0 Flash-Lite newer than Command R7B (12-2024)?
Gemini 2.0 Flash-Lite was released 2025-02-01; Command R7B (12-2024) was released 2024-12-13.
Go deeper
- Gemini 2.0 Flash-Lite: full specs, pricing and benchmarks
- Command R7B (12-2024): full specs, pricing and benchmarks
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