Qwen3.8-Flash-Next vs Sarvam-30B
Qwen3.8-Flash-Next leads the LLM Stats Score 49.7 to 19.9.
Alibaba Cloud / Qwen Team · Sarvam AI · Updated for 2026
Which is better?
Qwen3.8-Flash-Next leads the overall LLM Stats Score 49.7 to 19.9, ranking #15 overall.
In the 2 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 2; 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 Qwen3.8-Flash-Next
- overall performance matters — it scores 49.7 and ranks #15 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Aug 2026
Choose Sarvam-30B
- you are already invested in the Sarvam AI ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for Qwen3.8-Flash-Next · 14 for Sarvam-30B
Qwen3.8-Flash-Next outperforms in 2 benchmarks (GPQA, LiveCodeBench v6), while Sarvam-30B is better at 0 benchmarks.
Qwen3.8-Flash-Next significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3.8-Flash-Next has 95.0B more parameters than Sarvam-30B, making it 316.7% larger.
Input capabilities
Documented input modalities across available providers
Qwen3.8-Flash-Next supports multimodal inputs, whereas Sarvam-30B does not.
Qwen3.8-Flash-Next can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3.8-Flash-Next
Sarvam-30B
License
Usage and distribution terms
Qwen3.8-Flash-Next is licensed under Qwen Community License 1.0, while Sarvam-30B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Qwen Community License 1.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Qwen3.8-Flash-Next was released on 2026-08-26, while Sarvam-30B was released on 2026-03-06.
Qwen3.8-Flash-Next is 6 months newer than Sarvam-30B.
Aug 26, 2026
5 days ago
5mo newerMar 6, 2026
5 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Qwen3.8-Flash-Next and Sarvam-30B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3.8-Flash-Next vs Sarvam-30B.