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Beam 1.0 vs DeepSeek-V4.1-Flash-1017

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 44.6. DeepSeek-V4.1-Flash-1017 is 1.1x cheaper per token.

Reflection AI · DeepSeek · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 44.6, ranking #15 overall.

In the 3 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V4.1-Flash-1017 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 Beam 1.0

  • you want predictable pricing at $0.40/M input and $1.20/M output

Choose DeepSeek-V4.1-Flash-1017

  • overall performance matters — it scores 51.2 and ranks #15 on LLM Stats
  • your work emphasizes coding and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • cost matters — it's about 1.1x cheaper per token
  • you want the most recent training data — it shipped Oct 2026

At a glance

The differences that matter most.

Beam 1.0
Reflection AI
DeepSeek-V4.1-Flash-1017
DeepSeek
Core performance indexes
LLM Stats Score
44.6
#46
51.2
#15
Reasoning
45.5
#37
48.8
#18
Coding
33.7
#39
39.3
#14
Agents
28.8
#53
38.7
#8
Cost, coverage & limits
Benchmark wins
0 of 3
3 of 3
Input price
$0.40 / M
$0.30 / M
Output price
$1.20 / M
$1.20 / M
Context window
1,048,576
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
Beam 1.0
DeepSeek-V4.1-Flash-1017
Math
35.1#45
31.8#69
Vision
15.9#105
32.3#25
Tool use
26.4#32
31.3#6
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

22 reported for Beam 1.0 · 11 for DeepSeek-V4.1-Flash-1017

3 shared

Beam 1.0 outperforms in 0 benchmarks, while DeepSeek-V4.1-Flash-1017 is better at 3 benchmarks (AutomationBench, DeepSWE 1.1, Humanity's Last Exam).

DeepSeek-V4.1-Flash-1017 significantly outperforms across most benchmarks.

Wed Oct 21 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4.1-Flash-1017 costs less

For input processing, Beam 1.0 ($0.40/1M tokens) is 1.3x more expensive than DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens).

For output processing, Beam 1.0 ($1.20/1M tokens) costs the same as DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens).

In conclusion, Beam 1.0 is more expensive than DeepSeek-V4.1-Flash-1017.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Wed Oct 21 2026 • llm-stats.com
Reflection AI
Beam 1.0
Input tokens$0.40
Output tokens$1.20
Best providerTogether
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Notice missing or incorrect data?

Model Size

Parameter count comparison

261.9B diff

DeepSeek-V4.1-Flash-1017 has 261.9B more parameters than Beam 1.0, making it 52.2% larger.

Reflection AI
Beam 1.0
501.3Bparameters
DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
501.3B
Beam 1.0
763.2B
DeepSeek-V4.1-Flash-1017

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Beam 1.0 is limited to 131,072 tokens.

Reflection AI
Beam 1.0
Input1,048,576 tokens
Output131,072 tokens
DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Wed Oct 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Beam 1.0 does not.

DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Beam 1.0

Text
Images
Audio
Video

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

License

Usage and distribution terms

Beam 1.0 is licensed under Apache 2.0, while DeepSeek-V4.1-Flash-1017 uses MIT.

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

Beam 1.0

Apache 2.0

Open weights

DeepSeek-V4.1-Flash-1017

MIT

Open weights

Release Timeline

When each model was launched

Beam 1.0 was released on 2026-10-16, while DeepSeek-V4.1-Flash-1017 was released on 2026-10-17.

DeepSeek-V4.1-Flash-1017 is 0 month newer than Beam 1.0.

Beam 1.0

Oct 16, 2026

3 days ago

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

1d newer

Knowledge Cutoff

When training data ends

Beam 1.0 has a documented knowledge cutoff of 2026-06-30, while DeepSeek-V4.1-Flash-1017's cutoff date is not specified.

We can confirm Beam 1.0's training data extends to 2026-06-30, but cannot make a direct comparison without DeepSeek-V4.1-Flash-1017's cutoff date.

Beam 1.0

Jun 2026

DeepSeek-V4.1-Flash-1017

—

Provider Availability

Beam 1.0 is available from Together, Reflection AI. DeepSeek-V4.1-Flash-1017 is available from DeepSeek.

Beam 1.0

together logo
Together
Input Price:Input: $0.40/1MOutput Price:Output: $1.20/1M
reflection logo
Unknown Organization

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Beam 1.0 and DeepSeek-V4.1-Flash-1017 side-by-side, then vote on the output you prefer.

Beam 1.0
✓ Preferred
DeepSeek-V4.1-Flash-1017
Open in Playground

FAQ

Common questions about Beam 1.0 vs DeepSeek-V4.1-Flash-1017.

Which is better, Beam 1.0 or DeepSeek-V4.1-Flash-1017?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 44.6. Beam 1.0 is made by Reflection AI and DeepSeek-V4.1-Flash-1017 is made by DeepSeek. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Beam 1.0 compare to DeepSeek-V4.1-Flash-1017 in benchmarks?

Beam 1.0 scores AIME 2026: 97.7%, GPQA: 90.6%, LiveCodeBench: 88.3%, SWE-Bench Verified: 81.6%, MCP Atlas: 80.8%. DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%.

Is Beam 1.0 cheaper than DeepSeek-V4.1-Flash-1017?

DeepSeek-V4.1-Flash-1017 is 1.3x cheaper for input tokens. Beam 1.0 costs $0.40/M input and $1.20/M output via together. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek.

What are the context window sizes for Beam 1.0 and DeepSeek-V4.1-Flash-1017?

Beam 1.0 supports 1.0M tokens and DeepSeek-V4.1-Flash-1017 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 Beam 1.0 and DeepSeek-V4.1-Flash-1017?

Key differences include LLM Stats Score (44.6 vs 51.2), input pricing ($0.40 vs $0.30/M), multimodal support (no vs yes), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Beam 1.0 and DeepSeek-V4.1-Flash-1017?

Beam 1.0 is developed by Reflection AI and DeepSeek-V4.1-Flash-1017 is developed by DeepSeek.

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