Decision summary
- Voice agents and high QPS chat -> Sarvam 30B
- Long documents and harder agents -> Sarvam 105B
- 64K is enough -> Sarvam 30B
- 128K required -> Sarvam 105B
- Global frontier English-only -> evaluate other models too
Indic open-weight comparison
Frontier comparisonSarvam 30B vs Sarvam 105B
Sarvam 30B and Sarvam 105B are Apache 2.0 MoE chat models from Sarvam AI for Indian-language and English workloads.
Featured · Updated 6 weeks ago · Last verified: September 2026
Choose Sarvam 30B when
High-throughput Indic chat, support assistants, and voice-agent backends.
Choose Sarvam 105B when
Flagship Indic reasoning, coding, long-document analysis, and agent workflows.
- Voice agents and high QPS chat: Sarvam 30B
- Long documents and harder agents: Sarvam 105B
- 64K is enough: Sarvam 30B
Decision axes: Best for · Architecture · Context window · Indic fit
Reasoning
105B for harder reasoning; 30B for latency-sensitive lanes.
Coding
Reproduce coding tasks on both; vendor SWE numbers differ by size.
Multimodal
Text-only on both catalog rows.
Speed
2.4B active vs larger flagship active compute.
Enterprise
Data residency and sovereign AI narratives favor either; size is the split.
Curated matrix for Sarvam 30B vs Sarvam 105B — confirm live limits and pricing on each vendor’s official pages.
How they compare
Criterion-by-criterion notes from the catalog—not a ranking. Validate on your own gold set.
| Criterion | Sarvam 30B | Sarvam 105B |
|---|---|---|
| Best for | High-throughput Indic chat, support assistants, and voice-agent backends. | Flagship Indic reasoning, coding, long-document analysis, and agent workflows. |
| Architecture | 30B MoE with 2.4B active parameters per token; 16T-token pretrain noted by Sarvam. | 105B+ MoE flagship; higher active compute than 30B. |
| Context window | 64K context window. | 128K context window. |
| Indic fit | Optimized for Indian languages and English; vendor reports strong Indic win rates. | India-focused multilingual reasoning; powers Indus per Sarvam. |
| Agents and tools | OpenAI-compatible chat API; tool calling documented. | Tool use and agentic workflows emphasized on the flagship. |
| Deployment | Apache 2.0 open weights. | Apache 2.0 open weights; OpenAI-compatible API. |
| Latency and cost | Lower active compute than 105B; better fit for real-time lanes. | Heavier serve; better when quality beats throughput. |
| Operational risk | Vendor benchmarks; thinking mode can consume output budget. | Thinking on by default in docs; tune max_tokens and reasoning settings. |
Key insights
Concrete technical or product signals.
- In-family comparison only; not Sarvam 105B vs DeepSeek-R1.
- Both Apache 2.0; choose on active parameters and context, not license.
- Reproduce Indic evals with native script, romanized, and code-mixed inputs.
Use cases
Where this shines in production.
- Picking Sarvam size for Indic enterprise assistants
- Voice-agent backend vs document reasoning default
- Cost-aware Indic MoE deployment
Limitations & trade-offs
What to watch for.
- Vendor-reported Indic and agent benchmarks.
- Global English-only benchmarks understate Indic value and overstate gaps.
- Self-host ops still required for open weights.
Watch-outs
Who should pass, and what to validate before rollout.
- Do not choose 30B for hardest agent benchmarks without testing 105B.
- Do not choose 105B for lowest-latency voice without cost modeling.
- Do not treat as Sarvam vs DeepSeek—that is a separate page.
Final recommendation
What to do after reading the table.
Default 30B for user-facing chat and voice. Default 105B for back-office analysis and agents.
FAQ
Is Sarvam 30B better than Sarvam 105B?
Default 30B for user-facing chat and voice. Default 105B for back-office analysis and agents.
Which is better for coding: Sarvam 30B or Sarvam 105B?
Sarvam 30B: OpenAI-compatible chat API; tool calling documented. Sarvam 105B: Tool use and agentic workflows emphasized on the flagship. The catalog does not declare a winner on agents and tools.
Which is cheaper: Sarvam 30B or Sarvam 105B?
Listed unit prices: Sarvam 30B Lower active compute than 105B; better fit for real-time lanes; Sarvam 105B Heavier serve; better when quality beats throughput. A lower listed unit price is not the same as a lower total workload cost—tokens, session minutes, caching, introductory rates, and add-on modes can reverse the ranking. Confirm live rates on each vendor’s official page.
Can I use both Sarvam 30B and Sarvam 105B?
Yes. Many teams keep both and route by constraint. Use Sarvam 30B for High-throughput Indic chat, support assistants, and voice-agent backends, and Sarvam 105B for Flagship Indic reasoning, coding, long-document analysis, and agent workflows. Confirm vendor terms before mixing them in one production workflow.