Sarvam 105B vs Command R7B
Sarvam 105B comes out ahead, 65 to 62 on our weighted score, though Command R7B is 20% cheaper per token.
- Our pick
Sarvam AI
Sarvam 105B
65/100- ECI—
- Price$0.047 / $0.186
- Context131K
CohereCommand R7B
62/100- ECI—
- Price$0.037 / $0.15
- Context128K
Add a model
Make it a three-way comparison.
Sarvam 105B is our pick
Sarvam 105B is the better all-round choice, scoring 65/100 against Command R7B (62). It leads on inputs & features. 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 R7BCommand R7B $0.066 · Sarvam 105B $0.082 per 1M tokens (3:1 blend)
- Longest contextSarvam 105BSarvam 105B 131,072 · Command R7B 128,000 tokens
- Widest inputsSame inputsSarvam 105B: Text · Command R7B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Sarvam 105B | Command R7B |
|---|---|---|---|
| Price | 50% | 100 | 100 |
| Inputs & features | 30% | 35 | 25 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 65/100 | 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 | Sarvam 105BSarvam AI | Command R7BCohere |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.047 | $0.037 (best) |
| Output | $0.186 | $0.15 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.082 | $0.066 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Official Cohere API |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 4,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes · low · medium · high | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | sarvam-105b | command-r7b-12-2024 |
| API providers | 3 | 5 (best) |
| Released | Sep 1, 2025 | Dec 2, 2024 |
| Knowledge cutoff | — | Jun 1, 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Sarvam 105B$0.842
- Command R7B$0.675
Which should you choose?
Which is better: Sarvam 105B or Command R7B?
Sarvam 105B is the better all-round choice, scoring 65/100 against Command R7B (62). It leads on inputs & features. 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, Sarvam 105B or Command R7B?
Command R7B is cheaper at $0.037 input / $0.15 output per million tokens (official Cohere API price). Sarvam 105B costs $0.047 input / $0.186 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 versus $0.082 for Sarvam 105B (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Sarvam 105B has not been scored yet and Command R7B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Sarvam 105B and Command R7B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Sarvam 105B has the largest context window at 131,072 tokens, against 128,000 for Command R7B. Maximum output per response: Sarvam 105B up to 131,072, Command R7B up to 4,000 tokens.
Which can read images, PDFs, audio or video?
Sarvam 105B accepts text; Command R7B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Sarvam 105B is the newest, released Sep 1, 2025. Command R7B came out Dec 2, 2024. Knowledge cutoff: Command R7B Jun 1, 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.
