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DeepSeek-V4.1-Flash-1017 vs Phi-3.5-mini-instruct

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -4.1. Phi-3.5-mini-instruct is 5.2x cheaper per token.

DeepSeek · Microsoft · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to -4.1, ranking #15 overall.

On price, Phi-3.5-mini-instruct is roughly 5.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017

  • overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Oct 2026

Choose Phi-3.5-mini-instruct

  • cost matters — it's about 5.2x cheaper per token

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Phi-3.5-mini-instruct
Microsoft
Core performance indexes
LLM Stats Score
51.0
#15
-4.1
#370
Reasoning
48.6
#18
-5.0
#366
Coding
39.1
#15
-6.9
#284
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
$0.10 / M
Output price
$1.20 / M
$0.10 / M
Context window
1,048,576
128,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
Phi-3.5-mini-instruct
Math
31.8#67
-1.5#316
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 31 for Phi-3.5-mini-instruct

No common benchmarks found

DeepSeek-V4.1-Flash-1017 and Phi-3.5-mini-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Phi-3.5-mini-instruct costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 3.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 12.0x more expensive than Phi-3.5-mini-instruct ($0.10/1M tokens).

In conclusion, DeepSeek-V4.1-Flash-1017 is more expensive than Phi-3.5-mini-instruct.*

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

Lowest available price from all providers
Mon Oct 19 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Microsoft
Phi-3.5-mini-instruct
Input tokens$0.10
Output tokens$0.10
Best providerAzure
Notice missing or incorrect data?

Model Size

Parameter count comparison

759.4B diff

DeepSeek-V4.1-Flash-1017 has 759.4B more parameters than Phi-3.5-mini-instruct, making it 19984.4% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Microsoft
Phi-3.5-mini-instruct
3.8Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
3.8B
Phi-3.5-mini-instruct

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash-1017 accepts 1,048,576 input tokens compared to Phi-3.5-mini-instruct's 128,000 tokens. DeepSeek-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Phi-3.5-mini-instruct is limited to 128,000 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Microsoft
Phi-3.5-mini-instruct
Input128,000 tokens
Output128,000 tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas Phi-3.5-mini-instruct does not.

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

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Phi-3.5-mini-instruct

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-V4.1-Flash-1017

MIT

Open weights

Phi-3.5-mini-instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Phi-3.5-mini-instruct was released on 2024-08-23.

DeepSeek-V4.1-Flash-1017 is 26 months newer than Phi-3.5-mini-instruct.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

2 days ago

2.2yr newer
Phi-3.5-mini-instruct

Aug 23, 2024

2.2 years ago

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

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. Phi-3.5-mini-instruct is available from Azure.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Phi-3.5-mini-instruct

azure logo
Azure
Input Price:Input: $0.10/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Phi-3.5-mini-instruct side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Phi-3.5-mini-instruct
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Phi-3.5-mini-instruct.

Which is better, DeepSeek-V4.1-Flash-1017 or Phi-3.5-mini-instruct?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to -4.1. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Phi-3.5-mini-instruct is made by Microsoft. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash-1017 compare to Phi-3.5-mini-instruct in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. Phi-3.5-mini-instruct scores GSM8k: 86.2%, ARC-C: 84.6%, RULER: 84.1%, PIQA: 81.0%, OpenBookQA: 79.2%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Phi-3.5-mini-instruct?

Phi-3.5-mini-instruct is 3.0x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Phi-3.5-mini-instruct costs $0.10/M input and $0.10/M output via azure.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Phi-3.5-mini-instruct?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Phi-3.5-mini-instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash-1017 and Phi-3.5-mini-instruct?

Key differences include LLM Stats Score (51.0 vs -4.1), context window (1.0M vs 128K), input pricing ($0.30 vs $0.10/M), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Phi-3.5-mini-instruct?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Phi-3.5-mini-instruct is developed by Microsoft.

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