Sarvam 30B
nano-gpt/sarvam-30b제공: nano-gpt · 출시 2026-05-12
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
기능
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding51
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)0/20
- Provider availability1/10
Agents51
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit0/15
- Provider availability1/10
JSON / structured output40
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control0/10
- Price-friendly for high-volume20/20
Cost efficiency88
- Headline price (log-scaled)83/95
- Has prompt-cache pricing5/5
Long context0
- Context ≥ 100K0/100
Production-readiness65
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.20 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $0.39 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.11 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $0.34 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $0.40 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
가격 상세
추천 가격 제공자: nano-gpt · sarvam-30b
1곳 제공사에서 이용 가능
| 제공자 | 제공자 모델 ID | 입력 / 1M | 출력 / 1M | 컨텍스트 | 출시일 |
|---|---|---|---|---|---|
| NanoGPT nano-gpt | sarvam-30b | $0.028 | $0.111 | 66K | 2026-05-12 |
Frequently asked questions
How much does Sarvam 30B cost?
Sarvam 30B costs $0.028 per 1M input tokens and $0.111 per 1M output tokens, sourced from nano-gpt. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Sarvam 30B?
Sarvam 30B has a context window of 66K tokens, with a max output of 4K tokens per reply. This is the total combined size of prompt + completion.
Does Sarvam 30B support tool calling?
Yes. Sarvam 30B supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Sarvam 30B support structured output / JSON mode?
No. Sarvam 30B does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.
Can Sarvam 30B accept image input?
No. Sarvam 30B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Sarvam 30B open-weight?
No. Sarvam 30B is a proprietary model — only nano-gpt (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Sarvam 30B?
If Sarvam 30B doesn't fit, consider v0 1.5 LG, v0 1.0 MD, Auto model (Basic). Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More nano-gpt models
- v0 1.5 LG$15.00 in / $75.00 out
- v0 1.0 MD$3.00 in / $15.00 out
- Auto model (Basic)$10.00 in / $19.99 out
- Jamba Large$1.99 in / $7.99 out
- Hunyuan Turbo S$0.19 in / $0.37 out
Capability lists this model is in
마지막 업데이트:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.