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MiMo-V2.5-Pro vs Sarvam-30B

MiMo-V2.5-Pro leads the LLM Stats Score 24.7 to 19.6.

Xiaomi · Sarvam AI · Updated for 2026

Which is better?

MiMo-V2.5-Pro leads the overall LLM Stats Score 24.7 to 19.6, ranking #161 overall.

In the 5 individual benchmarks reported for both models, MiMo-V2.5-Pro wins 3; 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 MiMo-V2.5-Pro

  • overall performance matters — it scores 24.7 and ranks #161 on LLM Stats
  • your work emphasizes coding and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 5 exact shared results
  • you want the most recent training data — it shipped Apr 2026

Choose Sarvam-30B

  • you are already invested in the Sarvam AI ecosystem

At a glance

The differences that matter most.

Core performance indexes
24.7
#161
19.6
#202
24.1
#159
19.3
#200
31.0
#47
5.9
#193
22.1
#58
-1.4
#176
Cost, coverage & limits
Benchmark wins
3 of 5
2 of 5
Input price
$0.43 / M
— / M
Output price
$0.87 / M
— / M
Context window
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
MiMo-V2.5-Pro
Sarvam-30B
25.4#111
23.6#125
20.7#80
18.2#99
17.2#92
18.2#85
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

31 reported for MiMo-V2.5-Pro · 14 for Sarvam-30B

5 shared

MiMo-V2.5-Pro outperforms in 3 benchmarks (GPQA, MMLU, SWE-Bench Verified), while Sarvam-30B is better at 2 benchmarks (LiveCodeBench v6, MMLU-Pro).

MiMo-V2.5-Pro has a slight edge in benchmark performance.

Wed Sep 16 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

993.2B diff

MiMo-V2.5-Pro has 993.2B more parameters than Sarvam-30B, making it 3310.8% larger.

Xiaomi
MiMo-V2.5-Pro
1.0Tparameters
Sarvam AI
Sarvam-30B
30.0Bparameters
1023.2B
MiMo-V2.5-Pro
30.0B
Sarvam-30B

Context Window

Maximum input and output token capacity

Only MiMo-V2.5-Pro specifies input context (1,048,576 tokens). Only MiMo-V2.5-Pro specifies output context (131,072 tokens).

Xiaomi
MiMo-V2.5-Pro
Input1,048,576 tokens
Output131,072 tokens
Sarvam AI
Sarvam-30B
Input- tokens
Output- tokens
Wed Sep 16 2026 • llm-stats.com

License

Usage and distribution terms

MiMo-V2.5-Pro is licensed under MIT, while Sarvam-30B uses Apache 2.0.

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

MiMo-V2.5-Pro

MIT

Open weights

Sarvam-30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

MiMo-V2.5-Pro was released on 2026-04-27, while Sarvam-30B was released on 2026-03-06.

MiMo-V2.5-Pro is 2 months newer than Sarvam-30B.

MiMo-V2.5-Pro

Apr 27, 2026

4 months ago

1mo newer
Sarvam-30B

Mar 6, 2026

6 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?Start an Issue discussion

Judge for yourself.

Run your own prompts against MiMo-V2.5-Pro and Sarvam-30B side-by-side, then vote on the output you prefer.

MiMo-V2.5-Pro
✓ Preferred
Sarvam-30B
Open in Playground

FAQ

Common questions about MiMo-V2.5-Pro vs Sarvam-30B.

Which is better, MiMo-V2.5-Pro or Sarvam-30B?

MiMo-V2.5-Pro leads the LLM Stats Score 24.7 to 19.6. MiMo-V2.5-Pro is made by Xiaomi and Sarvam-30B 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 MiMo-V2.5-Pro compare to Sarvam-30B in benchmarks?

MiMo-V2.5-Pro scores FrontierSWE (Impl.): 100.0%, GSM8k: 99.6%, ARC-C: 97.2%, MMLU-Redux: 92.8%, C-Eval: 91.5%. Sarvam-30B scores MATH-500: 97.0%, AIME 2025: 96.7%, MBPP: 92.7%, HumanEval: 92.1%, MMLU: 85.1%.

What are the context window sizes for MiMo-V2.5-Pro and Sarvam-30B?

MiMo-V2.5-Pro supports 1.0M tokens and Sarvam-30B 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 MiMo-V2.5-Pro and Sarvam-30B?

Key differences include LLM Stats Score (24.7 vs 19.6), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes MiMo-V2.5-Pro and Sarvam-30B?

MiMo-V2.5-Pro is developed by Xiaomi and Sarvam-30B is developed by Sarvam AI.