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Model profile

Sarvam 30B

SarvamCurrentReleased Mar 6, 2026
Data verified
Overall Score
40.7Public #169 of 200
Arena Elo
Not listed
Eligible category ranks
0of 8
Price (1M tokens)
$0 in / $0 out
API pricing
Speed
Not listed
Context
64K

Evidence coverage

11 of 323 tracked benchmarks are published. 0 are verified and 11 provisional. 5 of 8 categories are measured.

Updated July 23, 2026Methodology
Published / tracked
11 / 323
Verified
0
Provisional
11
Categories with evidence
5 / 8

Evidence by category

  • Agentic1 benchmark
    Reported
  • Coding1 benchmark
    Reported
  • Reasoning2 benchmarks
    Reported
  • Knowledge6 benchmarks
    Reported
  • Math0 benchmarks
    Not measured
  • Multilingual0 benchmarks
    Not measured
  • Multimodal0 benchmarks
    Not measured
  • Inst. Following1 benchmark
    Reported
Open WeightSelf-hostReasoning
Confidence:
Low
base

Sarvam 30B ranks #169 out of 200 models on the public leaderboard with an overall score of 40.7/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

Sarvam 30B is a open weight model with a 64K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.

This profile currently has 11 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 39.941.49

  1. GPT-4o
    OpenAI
    #16541.49
    GPT-4o is #165 with a score of 41.49.
    Compare
  2. LFM2.5-8B-A1B
    LiquidAI
    #16641.42
    LFM2.5-8B-A1B is #166 with a score of 41.42.
    Compare
  3. Claude 3 Opus
    Anthropic
    #16841.13
    Claude 3 Opus is #168 with a score of 41.13.
    Compare
  4. Sarvam 30BCurrent model
    Sarvam
    #16940.7
    Sarvam 30B is #169 with a score of 40.7.
  5. Grok 3 [Beta]
    xAI
    #17140.43
    Grok 3 [Beta] is #171 with a score of 40.43.
    Compare
  6. Ministral 3 8B (Reasoning)
    Mistral
    #17240.38
    Ministral 3 8B (Reasoning) is #172 with a score of 40.38.
    Compare
  7. Mistral 7B v0.3
    Mistral
    #17339.9
    Mistral 7B v0.3 is #173 with a score of 39.9.
    Compare

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

No eligible category percentile is available from the published evidence yet.

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank Not rankedWeight 22%1 benchmarkReported35.5
CodingRank Not rankedWeight 20%1 benchmarkReported34.0
ReasoningWeight 17%2 benchmarksReportedScore pending
KnowledgeRank Not rankedWeight 12%6 benchmarksReported80.0
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalWeight 12%0 benchmarksNot measuredNot measured
Inst. FollowingWeight 5%1 benchmarkReportedScore pending

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Agentic1 benchmark
τ²-bench resultsReported

τ²-Bench Tool-Agent-User Evaluation

34.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Coding1 benchmark
AA-SciCodeReported

Artificial Analysis SciCode

19.2%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Reasoning2 benchmarks
AA-LCRReported

Artificial Analysis Long Context Reasoning

0.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
CritPtReported

Critical Physics Tasks

0.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Knowledge6 benchmarks
Artificial Analysis Intelligence IndexReported
6.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-GPQA DiamondReported

Artificial Analysis GPQA Diamond

63.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-HLEReported

Artificial Analysis Humanity's Last Exam

7.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience IndexReported

Artificial Analysis Omniscience Index

-72.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience AccuracyReported

Artificial Analysis Omniscience Accuracy

12.7%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience Hallucination RateReported

Artificial Analysis Omniscience Hallucination Rate

97.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Inst. Following1 benchmark
AA-IFBenchReported

Artificial Analysis IFBench

26.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.

Frequently Asked Questions

How does Sarvam 30B perform overall in AI benchmarks?

Sarvam 30B has 11 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is Sarvam 30B good for knowledge and understanding?

Sarvam 30B has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.

Is Sarvam 30B good for coding and programming?

Sarvam 30B has visible benchmark coverage in coding and programming, but BenchLM does not currently assign it a global category rank there.

Is Sarvam 30B good for reasoning and logic?

Sarvam 30B has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is Sarvam 30B good for agentic tool use and computer tasks?

Sarvam 30B has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.

Is Sarvam 30B good for instruction following?

Sarvam 30B has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.

Is Sarvam 30B open source?

Yes, Sarvam 30B is an open weight model created by Sarvam, meaning it can be downloaded and run locally or fine-tuned for specific use cases.

Does Sarvam 30B have full benchmark coverage on BenchLM?

Not yet. Sarvam 30B currently has 11 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of Sarvam 30B?

Sarvam 30B has a published context window of 64K, which determines how much text it can process in a single interaction.

Last updated: July 23, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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