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Mercury 3 vs Sarvam-105B

Mercury 3 leads the LLM Stats Score 36.1 to 25.2.

Inception · Sarvam AI · Updated for 2026

Which is better?

Mercury 3 leads the overall LLM Stats Score 36.1 to 25.2, ranking #98 overall.

In the 1 individual benchmarks reported for both models, Mercury 3 wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Mercury 3

  • overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Oct 2026

Choose Sarvam-105B

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Mercury 3
Inception
Sarvam-105B
Sarvam AI
Core performance indexes
LLM Stats Score
36.1
#98
25.2
#181
Reasoning
34.8
#103
25.7
#174
Coding
21.5
#105
-2.2
#273
Agents
19.4
#84
5.1
#170
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
$0.10 / M
— / M
Output price
$0.35 / M
— / M
Context window
1,000,000
—

Individual benchmarks

12 reported for Mercury 3 · 14 for Sarvam-105B

1 shared

Mercury 3 outperforms in 1 benchmarks (GPQA), while Sarvam-105B is better at 0 benchmarks.

Mercury 3 significantly outperforms across most benchmarks.

Fri Oct 23 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Mercury 3 specifies input context (1,000,000 tokens). Only Mercury 3 specifies output context (131,072 tokens).

Inception
Mercury 3
Input1,000,000 tokens
Output131,072 tokens
Sarvam AI
Sarvam-105B
Input- tokens
Output- tokens
Fri Oct 23 2026 • llm-stats.com

License

Usage and distribution terms

Mercury 3 is licensed under a proprietary license, while Sarvam-105B uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Mercury 3

Proprietary

Closed source

Sarvam-105B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Mercury 3 was released on 2026-10-19, while Sarvam-105B was released on 2026-03-06.

Mercury 3 is 8 months newer than Sarvam-105B.

Mercury 3

Oct 19, 2026

0 days ago

7mo newer
Sarvam-105B

Mar 6, 2026

7 months ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Mercury 3 and Sarvam-105B side-by-side, then vote on the output you prefer.

Mercury 3
✓ Preferred
Sarvam-105B
Open in Playground

FAQ

Common questions about Mercury 3 vs Sarvam-105B.

Which is better, Mercury 3 or Sarvam-105B?

Mercury 3 leads the LLM Stats Score 36.1 to 25.2. Mercury 3 is made by Inception and Sarvam-105B is made by Sarvam AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Mercury 3 compare to Sarvam-105B in benchmarks?

Mercury 3 scores GPQA: 89.2%, AA-LCR: 77.7%, IFBench: 76.8%, MRCR v2: 75.5%, DeepSearchQA: 71.3%. Sarvam-105B scores MATH-500: 98.6%, AIME 2025: 96.7%, MMLU: 90.6%, HMMT 2025: 85.8%, HMMT25: 85.8%.

What are the context window sizes for Mercury 3 and Sarvam-105B?

Mercury 3 supports 1.0M tokens and Sarvam-105B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Mercury 3 and Sarvam-105B?

Key differences include LLM Stats Score (36.1 vs 25.2), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Mercury 3 and Sarvam-105B?

Mercury 3 is developed by Inception and Sarvam-105B is developed by Sarvam AI.

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