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Qwen3 VL 235B A22B Thinking vs Sarvam-105B

Both models are evenly matched across the benchmarks.

Alibaba Cloud / Qwen Team · Sarvam AI · Updated for 2026

Which is better?

Qwen3 VL 235B A22B Thinking outperforms in 3 benchmarks (Humanity's Last Exam, IFEval, MMLU-Pro), while Sarvam-105B is better at 3 benchmarks (AIME 2025, HMMT25, LiveCodeBench v6). Both models are evenly matched across the benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose Qwen3 VL 235B A22B Thinking

  • you want predictable pricing at $0.45/M input and $3.49/M output

Choose Sarvam-105B

  • you want the strongest raw capability — it leads on 4 of 7 shared benchmarks
  • you want the most recent training data — it shipped Mar 2026

At a glance

The differences that matter most.

Benchmark wins
3 of 7
4 of 7
Input price
$0.45 / M
— / M
Output price
$3.49 / M
— / M
Context window
262,144
Released
Sep 2025
Mar 2026
License
Apache 2.0
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Qwen3 VL 235B A22B Thinking outperforms in 3 benchmarks (Humanity's Last Exam, IFEval, MMLU-Pro), while Sarvam-105B is better at 3 benchmarks (AIME 2025, HMMT25, LiveCodeBench v6).

Both models are evenly matched across the benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

131.0B diff

Qwen3 VL 235B A22B Thinking has 131.0B more parameters than Sarvam-105B, making it 124.8% larger.

Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
236.0Bparameters
Sarvam AI
Sarvam-105B
105.0Bparameters
236.0B
Qwen3 VL 235B A22B Thinking
105.0B
Sarvam-105B

Context Window

Maximum input and output token capacity

Only Qwen3 VL 235B A22B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Thinking specifies output context (262,144 tokens).

Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Sarvam AI
Sarvam-105B
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas Sarvam-105B does not.

Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3 VL 235B A22B Thinking

Text
Images
Audio
Video

Sarvam-105B

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3 VL 235B A22B Thinking

Apache 2.0

Open weights

Sarvam-105B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3 VL 235B A22B Thinking was released on 2025-09-22, while Sarvam-105B was released on 2026-03-06.

Sarvam-105B is 6 months newer than Qwen3 VL 235B A22B Thinking.

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

11 months ago

Sarvam-105B

Mar 6, 2026

5 months ago

5mo newer

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 Qwen3 VL 235B A22B Thinking and Sarvam-105B side-by-side, then vote on the output you prefer.

Qwen3 VL 235B A22B Thinking
✓ Preferred
Sarvam-105B
Open in Playground

FAQ

Common questions about Qwen3 VL 235B A22B Thinking vs Sarvam-105B.

Which is better, Qwen3 VL 235B A22B Thinking or Sarvam-105B?

Both models are evenly matched across the benchmarks. Qwen3 VL 235B A22B Thinking is made by Alibaba Cloud / Qwen Team and Sarvam-105B is made by Sarvam AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen3 VL 235B A22B Thinking compare to Sarvam-105B in benchmarks?

Qwen3 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%. 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 Qwen3 VL 235B A22B Thinking and Sarvam-105B?

Qwen3 VL 235B A22B Thinking supports 262K 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 Qwen3 VL 235B A22B Thinking and Sarvam-105B?

Key differences include multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes Qwen3 VL 235B A22B Thinking and Sarvam-105B?

Qwen3 VL 235B A22B Thinking is developed by Alibaba Cloud / Qwen Team and Sarvam-105B is developed by Sarvam AI.