Command R7B Arabic vs Sonar Deep Research vs Nova Micro
Too close to call on our weighted score (Command R7B Arabic 62, Nova Micro 62, Sonar Deep Research 20). The right pick depends on what you value most.
CohereCommand R7B Arabic
62/100- ECI—
- Price$0.037 / $0.15
- Context128K
PerplexitySonar Deep Research
20/100- ECI—
- Price$2.00 / $8.00
- Context128K
AmazonNova Micro
62/100- ECI—
- Price$0.035 / $0.14
- Context128K
Too close to call
It is close. Our weighted score puts them within a point (Command R7B Arabic 62/100, Nova Micro 62/100, Sonar Deep Research 20/100), so choose by what matters most for your work: Nova Micro 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 priceNova MicroNova Micro $0.061 · Command R7B Arabic $0.066 · Sonar Deep Research $3.50 per 1M tokens (3:1 blend)
- Longest contextAbout the sameCommand R7B Arabic 128,000 · Sonar Deep Research 128,000 · Nova Micro 128,000 tokens
- Widest inputsSame inputsCommand R7B Arabic: Text · Sonar Deep Research: Text · Nova Micro: Text
- Self-hostingCommand R7B ArabicPublishes downloadable weights
| Measure | Weight | Command R7B Arabic | Sonar Deep Research | Nova Micro |
|---|---|---|---|---|
| Price | 50% | 100 | 24 | 100 |
| Inputs & features | 30% | 25 | 10 | 25 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 62/100 | 20/100 | 62/100 |
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 | Command R7B ArabicCohere | Sonar Deep ResearchPerplexity | Nova MicroAmazon |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.037 | $2.00 | $0.035 (best) |
| Output | $0.15 | $8.00 | $0.14 (best) |
| Cached input | — | — | $0.0088 |
| Blended (3:1) | $0.066 | $3.50 | $0.061 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Cohere API | Official Perplexity API | Official Amazon Bedrock API |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 128,000 tokens |
| Max output | 4,000 tokens | 32,768 tokens (best) | 10,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yesminimal · low · medium · high | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | command-r7b-arabic-02-2025 | sonar-deep-research | amazon.nova-micro-v1:0 |
| API providers | 1 | 3 (best) | 3 (best) |
| Released | Feb 27, 2025 | Feb 1, 2025 | Dec 3, 2024 |
| Knowledge cutoff | Jun 1, 2024 | Jan 2025 | 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.
- Command R7B Arabic$0.675
- Sonar Deep Research$36.00
- Nova Micro$0.63
Which should you choose?
Which is better: Command R7B Arabic, Sonar Deep Research or Nova Micro?
It is close. Our weighted score puts them within a point (Command R7B Arabic 62/100, Nova Micro 62/100, Sonar Deep Research 20/100), so choose by what matters most for your work: Nova Micro 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, Command R7B Arabic, Sonar Deep Research or Nova Micro?
Nova Micro is cheaper at $0.035 input / $0.14 output per million tokens (official Amazon Bedrock API price). Command R7B Arabic costs $0.037 input / $0.15 output per million tokens (official Cohere API price); Sonar Deep Research costs $2.00 input / $8.00 output per million tokens (official Perplexity API price). At a typical mix of three input tokens to one output token, that is $0.061 per million tokens for Nova Micro versus $0.066 for Command R7B Arabic (1.1× as much) and $3.50 for Sonar Deep Research (57× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Command R7B Arabic has not been scored yet, Sonar Deep Research has not been scored yet and Nova Micro has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Command R7B Arabic, Sonar Deep Research and Nova Micro yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Sonar Deep Research does not support tool calling, which most coding agents need.
Which has the bigger context window?
Command R7B Arabic, Sonar Deep Research and Nova Micro share the same 128,000-token context window. Maximum output per response: Command R7B Arabic up to 4,000, Sonar Deep Research up to 32,768, Nova Micro up to 10,000 tokens.
Which can read images, PDFs, audio or video?
Command R7B Arabic accepts text; Sonar Deep Research accepts text; Nova Micro accepts text. They handle the same number of input types.
Are any of these open source?
Command R7B Arabic publishes its weights and can be self-hosted; Sonar Deep Research and Nova Micro is proprietary.
Which is newer?
Command R7B Arabic is the newest, released Feb 27, 2025. Sonar Deep Research came out Feb 1, 2025; Nova Micro came out Dec 3, 2024. Knowledge cutoff: Command R7B Arabic Jun 1, 2024, Sonar Deep Research Jan 2025, Nova Micro 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 Oct 4, 2026.
