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DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V4.1-Flash

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -3.0.

DeepSeek · DeepSeek · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to -3.0, ranking #12 overall.

In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; 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 DeepSeek R1 Distill Qwen 1.5B

  • you are already invested in the DeepSeek ecosystem

Choose DeepSeek-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #12 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek R1 Distill Qwen 1.5B
DeepSeek
DeepSeek-V4.1-Flash
DeepSeek
Core performance indexes
LLM Stats Score
-3.0
#341
51.8
#12
Reasoning
-2.6
#331
48.9
#17
Coding
-4.6
#258
44.4
#5
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
— / M
$0.22 / M
Output price
— / M
$0.66 / M
Context window
—
1,040,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek R1 Distill Qwen 1.5B
DeepSeek-V4.1-Flash
Math
5.4#271
35.2#43
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

4 reported for DeepSeek R1 Distill Qwen 1.5B · 20 for DeepSeek-V4.1-Flash

1 shared

DeepSeek R1 Distill Qwen 1.5B outperforms in 0 benchmarks, while DeepSeek-V4.1-Flash is better at 1 benchmark (GPQA).

DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.

Sat Sep 12 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

761.4B diff

DeepSeek-V4.1-Flash has 761.4B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 42776.7% larger.

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
1.8B
DeepSeek R1 Distill Qwen 1.5B
763.2B
DeepSeek-V4.1-Flash

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input- tokens
Output- tokens
DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Sat Sep 12 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek R1 Distill Qwen 1.5B

Text
Images
Audio
Video

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under MIT.

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

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

DeepSeek-V4.1-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20, while DeepSeek-V4.1-Flash was released on 2026-09-10.

DeepSeek-V4.1-Flash is 20 months newer than DeepSeek R1 Distill Qwen 1.5B.

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.6 years ago

DeepSeek-V4.1-Flash

Sep 10, 2026

2 days ago

1.6yr 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 DeepSeek R1 Distill Qwen 1.5B and DeepSeek-V4.1-Flash side-by-side, then vote on the output you prefer.

DeepSeek R1 Distill Qwen 1.5B
✓ Preferred
DeepSeek-V4.1-Flash
Open in Playground

FAQ

Common questions about DeepSeek R1 Distill Qwen 1.5B vs DeepSeek-V4.1-Flash.

Which is better, DeepSeek R1 Distill Qwen 1.5B or DeepSeek-V4.1-Flash?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to -3.0. DeepSeek R1 Distill Qwen 1.5B is made by DeepSeek and DeepSeek-V4.1-Flash is made by DeepSeek. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek R1 Distill Qwen 1.5B compare to DeepSeek-V4.1-Flash in benchmarks?

DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%. DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%.

What are the context window sizes for DeepSeek R1 Distill Qwen 1.5B and DeepSeek-V4.1-Flash?

DeepSeek R1 Distill Qwen 1.5B supports an unknown number of tokens and DeepSeek-V4.1-Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek R1 Distill Qwen 1.5B and DeepSeek-V4.1-Flash?

Key differences include LLM Stats Score (-3.0 vs 51.8), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

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