DeepSeek-V4-Flash-0731 vs Ling 3.0 Flash
DeepSeek-V4-Flash-0731 leads the LLM Stats Score 43.0 to 35.9. DeepSeek-V4-Flash-0731 and Ling 3.0 Flash cost the same.
DeepSeek · InclusionAI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 43.0 to 35.9, ranking #57 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4-Flash-0731 wins 1; this is a narrower head-to-head signal than the composite indexes.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- overall performance matters — it scores 43.0 and ranks #57 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
Choose Ling 3.0 Flash
- you want the most recent training data — it shipped Aug 2026
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 · 19 for Ling 3.0 Flash
DeepSeek-V4-Flash-0731 outperforms in 1 benchmarks (Terminal-Bench 2.1), while Ling 3.0 Flash 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 ($0.06/1M tokens) costs the same as Ling 3.0 Flash ($0.06/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) costs the same as Ling 3.0 Flash ($0.18/1M tokens).
In conclusion, DeepSeek-V4-Flash-0731 and Ling 3.0 Flash cost the same.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 180.0B more parameters than Ling 3.0 Flash, making it 145.2% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Ling 3.0 Flash's 131,072 tokens. DeepSeek-V4-Flash-0731 can generate longer responses up to 1,048,576 tokens, while Ling 3.0 Flash is limited to 131,072 tokens.
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0731 was released on 2026-07-31, while Ling 3.0 Flash was released on 2026-08-04.
Ling 3.0 Flash is 0 month newer than DeepSeek-V4-Flash-0731.
Jul 31, 2026
2 months ago
Aug 4, 2026
2 months ago
4d newerKnowledge 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. Ling 3.0 Flash is available from DeepInfra.
DeepSeek-V4-Flash-0731
Ling 3.0 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Ling 3.0 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Ling 3.0 Flash.