Model comparison

DeepSeek-V3.1 vs Phi-4 Mini

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 30.9 on the Noometry Index. Phi-4 Mini costs 3.2× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

Last verified October 10, 2026. 1 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

Phi-4 Mini

Microsoft

30.9

Rank #283 Reported

Summary

They share 1 benchmark with published results for both. DeepSeek-V3.1 scores higher in 3 categories and Phi-4 Mini in 0 categories; 3 gaps are clear of the uncertainty.
The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.7 to 25.3.
The biggest single-benchmark swing is Vectara Hallucination Rate: 5.5% for DeepSeek-V3.1 and 23.5% for Phi-4 Mini.
Phi-4 Mini is cheaper at $0.075 / $0.30 per million input/output tokens, against $0.25 / $0.95 for DeepSeek-V3.1.
DeepSeek-V3.1 accepts more context: 164K tokens versus 128K.

Side by side

DeepSeek-V3.1 and Phi-4 Mini specifications
	DeepSeek-V3.1	Phi-4 Mini
Provider	DeepSeek	Microsoft
Noometry Index	42.8	30.9
Released	2025-08-21	2024-12-11
Weights	Open	Open
Context window	164K	128K
Max output	8K	4K
Input $ / M tokens	$0.25	$0.075
Output $ / M tokens	$0.95	$0.30
Results tracked	27	3

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Category by category

Coding DeepSeek-V3.1 leads

DeepSeek-V3.1: 40.3 (#144), Phi-4 Mini: 28.1 (#317)

Coding benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
SciCode	—	10.8%
WeirdML	38.4%	—
LMArena Coding	1417	—

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.9 (#110), Phi-4 Mini: 22.4 (#195)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
SimpleBench	40%	—
Kagi LLM Benchmark	53.2%	—
CritPt	—	0%
LMArena Hard Prompts	1417	—
DTBench	82.7%	—
LMCA	24.3%	—
Epoch Capabilities Index	139.92	—
ForecastBench	58	—

Math Not comparable

DeepSeek-V3.1: 38.9 (#122), Phi-4 Mini: —

Math benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
LMArena Math	1420	—

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.7 (#90), Phi-4 Mini: 25.3 (#262)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
Vectara Hallucination Rate	5.5%	23.5%
LMArena Expert	1405	—

Multilingual Not comparable

DeepSeek-V3.1: 51.6 (#106), Phi-4 Mini: —

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
LMArena Non-English	1400	—
LMArena Chinese	1469	—
LMArena French	1447	—
LMArena German	1411	—
LMArena Japanese	1378	—
LMArena Korean	1337	—
LMArena Russian	1405	—
LMArena Spanish	1431	—

Instruction Following Not comparable

DeepSeek-V3.1: 73.9 (#110), Phi-4 Mini: —

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
LMArena Instruction Following	1400	—

Long Context Not comparable

DeepSeek-V3.1: 36.3 (#232), Phi-4 Mini: —

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
Fiction.LiveBench	52.8%	—
LMArena Longer Query	1422	—

Writing & Preference Not comparable

DeepSeek-V3.1: 60.3 (#98), Phi-4 Mini: —

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Phi-4 Mini
LMArena Text	1420	—
LMArena Creative Writing	1401	—
EQ-Bench Creative Writing	1436	—
LMArena Multi-Turn	1408	—

Frequently asked questions

Is DeepSeek-V3.1 better than Phi-4 Mini?

Which is cheaper, DeepSeek-V3.1 or Phi-4 Mini?

Phi-4 Mini is cheaper. It lists at $0.075 per million input tokens and $0.30 per million output tokens; DeepSeek-V3.1 lists at $0.25 and $0.95.

Is DeepSeek-V3.1 or Phi-4 Mini better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 versus 28.1 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 128K.

How many benchmarks do DeepSeek-V3.1 and Phi-4 Mini share?

1 benchmark has published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Phi-4 Mini has 3.