Gemini 2.0 Flash-Lite vs Command R7B Arabic vs Nova Lite
Gemini 2.0 Flash-Lite comes out ahead, 82 to 75 and 65 on our weighted score, though Command R7B Arabic is 41% cheaper per token.
- Our pick
Google
Gemini 2.0 Flash-Lite
82/100- ECI—
- Price$0.064 / $0.255
- Context1.05M
Cohere
Command R7B Arabic
65/100- ECI—
- Price$0.037 / $0.15
- Context128K
Amazon
Nova Lite
75/100- ECI—
- Price$0.06 / $0.24
- Context300K
Gemini 2.0 Flash-Lite is our pick
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Nova Lite (75) and Command R7B Arabic (65). It leads on inputs & features and context window. Command R7B Arabic wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceCommand R7B ArabicCommand R7B Arabic $0.066 · Nova Lite $0.105 · Gemini 2.0 Flash-Lite $0.111 per 1M tokens (3:1 blend)
- Longest contextGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite 1,048,576 · Nova Lite 300,000 · Command R7B Arabic 128,000 tokens
- Widest inputsGemini 2.0 Flash-LiteGemini 2.0 Flash-Lite: Text, Images, PDFs, Audio, Video · Command R7B Arabic: Text · Nova Lite: Text, Images, PDFs, Video
- Self-hostingCommand R7B ArabicPublishes downloadable weights
| Measure | Weight | Gemini 2.0 Flash-Lite | Command R7B Arabic | Nova Lite |
|---|---|---|---|---|
| Price | 50% | 91 | 100 | 92 |
| Inputs & features | 30% | 80 | 35 | 70 |
| Context window | 20% | 61 | 24 | 39 |
| Overall | 100% | 82/100 | 65/100 | 75/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.064 | $0.037 (best) | $0.06 |
| Output | $0.255 | $0.15 (best) | $0.24 |
| Cached input | — | — | $0.015 |
| Blended (3:1) | $0.111 | $0.066 (best) | $0.105 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official Cohere API | Official Amazon Bedrock API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 128,000 tokens | 300,000 tokens |
| Max output | 8,192 tokens | 4,000 tokens | 10,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | command-r7b-arabic-02-2025 | amazon.nova-lite-v1:0 |
| API providers | 3 | 1 | 8 (best) |
| Released | Dec 11, 2024 | Feb 27, 2025 | Dec 3, 2024 |
| Knowledge cutoff | Jun 2024 | Jun 1, 2024 | Oct 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Gemini 2.0 Flash-Lite$1.15
Command R7B Arabic$0.675
Nova Lite$1.08
Which should you choose?
Which is better: Gemini 2.0 Flash-Lite, Command R7B Arabic or Nova Lite?
Gemini 2.0 Flash-Lite is the better all-round choice, scoring 82/100 against Nova Lite (75) and Command R7B Arabic (65). It leads on inputs & features and context window. Command R7B Arabic wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Gemini 2.0 Flash-Lite, Command R7B Arabic or Nova Lite?
Command R7B Arabic is cheaper at $0.037 input / $0.15 output per million tokens (official Cohere API price). Nova Lite costs $0.06 input / $0.24 output per million tokens (official Amazon Bedrock API price); Gemini 2.0 Flash-Lite costs $0.064 input / $0.255 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.066 per million tokens for Command R7B Arabic versus $0.105 for Nova Lite (1.6× as much) and $0.111 for Gemini 2.0 Flash-Lite (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.0 Flash-Lite has not been scored yet, Command R7B Arabic has not been scored yet and Nova Lite has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.0 Flash-Lite, Command R7B Arabic and Nova Lite yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.0 Flash-Lite has the largest context window at 1,048,576 tokens, against 300,000 for Nova Lite and 128,000 for Command R7B Arabic. Maximum output per response: Gemini 2.0 Flash-Lite up to 8,192, Command R7B Arabic up to 4,000, Nova Lite up to 10,000 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.0 Flash-Lite accepts text, images, PDFs, audio and video; Command R7B Arabic accepts text; Nova Lite accepts text, images, PDFs and video. Gemini 2.0 Flash-Lite handles the widest range of inputs.
Are any of these open source?
Command R7B Arabic publishes its weights and can be self-hosted; Gemini 2.0 Flash-Lite and Nova Lite is proprietary.
Which is newer?
Command R7B Arabic is the newest, released Feb 27, 2025. Gemini 2.0 Flash-Lite came out Dec 11, 2024; Nova Lite came out Dec 3, 2024. Knowledge cutoff: Gemini 2.0 Flash-Lite Jun 2024, Command R7B Arabic Jun 1, 2024, Nova Lite Oct 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.