The AI arena is free today

Open Superagent

DeepSeek-V4-Flash-0731 vs LFM3-1.7B

DeepSeek-V4-Flash-0731 leads the LLM Stats Score 42.2 to 25.0.

DeepSeek · Liquid AI · Updated for 2026

Which is better?

DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 42.2 to 25.0, ranking #68 overall.

The models split the 2 individual benchmarks reported for both models evenly.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Flash-0731

  • overall performance matters — it scores 42.2 and ranks #68 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes

Choose LFM3-1.7B

  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

DeepSeek-V4-Flash-0731
DeepSeek
LFM3-1.7B
Liquid AI
Core performance indexes
LLM Stats Score
42.2
#68
25.0
#191
Reasoning
39.9
#72
20.8
#216
Coding
31.0
#63
7.4
#218
Agents
28.4
#60
18.1
#97
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
1,048,576
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4-Flash-0731
LFM3-1.7B
Tool use
23.0#56
14.3#118
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

9 reported for DeepSeek-V4-Flash-0731 · 20 for LFM3-1.7B

2 shared

DeepSeek-V4-Flash-0731 outperforms in 1 benchmarks (Terminal-Bench 2.1), while LFM3-1.7B is better at 1 benchmark (AutomationBench).

Both models are evenly matched across the benchmarks.

Wed Nov 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

302.3B diff

DeepSeek-V4-Flash-0731 has 302.3B more parameters than LFM3-1.7B, making it 17472.3% larger.

DeepSeek
DeepSeek-V4-Flash-0731
304.0Bparameters
Liquid AI
LFM3-1.7B
1.7Bparameters
304.0B
DeepSeek-V4-Flash-0731
1.7B
LFM3-1.7B

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (1,048,576 tokens).

DeepSeek
DeepSeek-V4-Flash-0731
Input1,048,576 tokens
Output1,048,576 tokens
Liquid AI
LFM3-1.7B
Input- tokens
Output- tokens
Wed Nov 04 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V4-Flash-0731 is licensed under MIT, while LFM3-1.7B uses LFM Open License v1.0.

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

DeepSeek-V4-Flash-0731

MIT

Open weights

LFM3-1.7B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-0731 was released on 2026-07-31, while LFM3-1.7B was released on 2026-10-27.

LFM3-1.7B is 3 months newer than DeepSeek-V4-Flash-0731.

DeepSeek-V4-Flash-0731

Jul 31, 2026

3 months ago

LFM3-1.7B

Oct 27, 2026

1 weeks ago

2mo 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?

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-0731 and LFM3-1.7B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-0731
✓ Preferred
LFM3-1.7B
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-0731 vs LFM3-1.7B.

Which is better, DeepSeek-V4-Flash-0731 or LFM3-1.7B?

DeepSeek-V4-Flash-0731 leads the LLM Stats Score 42.2 to 25.0. DeepSeek-V4-Flash-0731 is made by DeepSeek and LFM3-1.7B is made by Liquid AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4-Flash-0731 compare to LFM3-1.7B in benchmarks?

DeepSeek-V4-Flash-0731 scores Terminal-Bench 2.1: 82.7%, CyberGym: 76.7%, Toolathlon: 70.3%, DSBench-FullStack: 68.7%, DSBench-Hard: 59.6%. LFM3-1.7B scores IFEval: 96.7%, Multi-IF: 89.1%, LiveCodeBench v6: 73.5%, IFBench: 73.0%, BFCL-V4: 71.4%.

What are the context window sizes for DeepSeek-V4-Flash-0731 and LFM3-1.7B?

DeepSeek-V4-Flash-0731 supports 1.0M tokens and LFM3-1.7B 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 DeepSeek-V4-Flash-0731 and LFM3-1.7B?

Key differences include LLM Stats Score (42.2 vs 25.0), licensing (MIT vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-0731 and LFM3-1.7B?

DeepSeek-V4-Flash-0731 is developed by DeepSeek and LFM3-1.7B is developed by Liquid AI.

Related comparisons