DeepSeek-V4-Flash-0731 vs Laguna S 2.1
DeepSeek-V4-Flash-0731 and Laguna S 2.1 are closely matched at 46.1 and 41.4 on the LLM Stats Score. DeepSeek-V4-Flash-0731 is 1.1x cheaper per token.
DeepSeek · Poolside · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 and Laguna S 2.1 are closely matched on the overall LLM Stats Score at 46.1 and 41.4.
In the 2 individual benchmarks reported for both models, DeepSeek-V4-Flash-0731 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4-Flash-0731 is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 1.1x cheaper per token
- you want the most recent training data — it shipped Jul 2026
Choose Laguna S 2.1
- you want predictable pricing at $0.10/M input and $0.20/M output
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
9 reported for DeepSeek-V4-Flash-0731 · 6 for Laguna S 2.1
DeepSeek-V4-Flash-0731 outperforms in 2 benchmarks (Terminal-Bench 2.1, Toolathlon), while Laguna S 2.1 is better at 0 benchmarks.
DeepSeek-V4-Flash-0731 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 1.1x cheaper than Laguna S 2.1 ($0.10/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 1.1x cheaper than Laguna S 2.1 ($0.20/1M tokens).
In conclusion, Laguna S 2.1 is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 186.0B more parameters than Laguna S 2.1, making it 157.6% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Only DeepSeek-V4-Flash-0731 specifies output context (384,000 tokens).
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 is licensed under MIT, while Laguna S 2.1 uses OpenMDW License v1.1.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
OpenMDW License v1.1
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Laguna S 2.1 was released on 2026-07-21.
DeepSeek-V4-Flash-0731 is 0 month newer than Laguna S 2.1.
Jul 31, 2026
4 weeks ago
1w newerJul 21, 2026
1 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Novita, Fireworks. Laguna S 2.1 is available from Poolside.
DeepSeek-V4-Flash-0731
Laguna S 2.1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Laguna S 2.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Laguna S 2.1.