Model comparison

Phi-4 Mini vs Qwen3.8 27B

Qwen3.8 27B is the stronger model overall, scoring 46.0 to 30.9 on the Noometry Index. Phi-4 Mini costs 4.6× less per token, which makes it the better buy when Qwen3.8 27B's lead doesn't matter for your workload.

Last verified October 11, 2026. 2 shared benchmarks.

Phi-4 Mini

Microsoft

30.9

Rank #283 Reported

Qwen3.8 27B

Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

They share 2 benchmarks with published results for both. Phi-4 Mini scores higher in 0 categories and Qwen3.8 27B in 3 categories; 3 gaps are clear of the uncertainty.
The widest gap is in coding, where Qwen3.8 27B leads 50.5 to 28.1.
The biggest single-benchmark swing is SciCode: 10.8% for Phi-4 Mini and 46.6% for Qwen3.8 27B.
Phi-4 Mini is cheaper at $0.075 / $0.30 per million input/output tokens, against $0.04 / $2.30 for Qwen3.8 27B.
Qwen3.8 27B accepts more context: 262K tokens versus 128K.

Side by side

Phi-4 Mini and Qwen3.8 27B specifications
	Phi-4 Mini	Qwen3.8 27B
Provider	Microsoft	Alibaba (Qwen)
Noometry Index	30.9	46.0
Released	2024-12-11	2026-08-14
Weights	Open	Open
Context window	128K	262K
Max output	4K	33K
Input $ / M tokens	$0.075	$0.04
Output $ / M tokens	$0.30	$2.30
Results tracked	3	31

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Category by category

Coding Qwen3.8 27B leads

Phi-4 Mini: 28.1 (#317), Qwen3.8 27B: 50.5 (#44)

Coding benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
SciCode	10.8%	46.6%
LMArena WebDev	—	1593
LMArena Coding	—	1482

Agentic & Tool Use Not comparable

Phi-4 Mini: —, Qwen3.8 27B: 32.9 (#57)

Agentic & Tool Use benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
APEX-Agents	—	47.5%

Reasoning Qwen3.8 27B leads

Phi-4 Mini: 22.4 (#195), Qwen3.8 27B: 41.0 (#54)

Reasoning benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
CritPt	0%	5.4%
ARC-AGI-2	—	42.4%
NYT Connections (extended)	—	54.5%
ARC-AGI-1	—	87.5%
LMArena Hard Prompts	—	1460
DTBench	—	88%
LMCA	—	41.4%
Surface Evolver Bench	—	45%
Epoch Capabilities Index	—	149.38

Math Not comparable

Phi-4 Mini: —, Qwen3.8 27B: 37.1 (#161)

Math benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
ProofBench	—	16%
LMArena Math	—	1456

Knowledge Qwen3.8 27B leads

Phi-4 Mini: 25.3 (#262), Qwen3.8 27B: 41.6 (#109)

Knowledge benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
Vectara Hallucination Rate	23.5%	—
LMArena Expert	—	1482

Multimodal Not comparable

Phi-4 Mini: —, Qwen3.8 27B: 41.3 (#37)

Multimodal benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
LMArena Vision	—	1271

Multilingual Not comparable

Phi-4 Mini: —, Qwen3.8 27B: 53.7 (#60)

Multilingual benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
LMArena Non-English	—	1430
LMArena Chinese	—	1504
LMArena French	—	1465
LMArena German	—	1438
LMArena Japanese	—	1384
LMArena Korean	—	1393
LMArena Russian	—	1415
LMArena Spanish	—	1448

Instruction Following Not comparable

Phi-4 Mini: —, Qwen3.8 27B: 75.8 (#53)

Instruction Following benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
LMArena Instruction Following	—	1439

Long Context Not comparable

Phi-4 Mini: —, Qwen3.8 27B: 44.3 (#70)

Long Context benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
LMArena Longer Query	—	1450

Writing & Preference Not comparable

Phi-4 Mini: —, Qwen3.8 27B: 65.8 (#43)

Writing & Preference benchmarks
Benchmark	Phi-4 Mini	Qwen3.8 27B
LMArena Text	—	1441
LMArena Creative Writing	—	1384
EQ-Bench Creative Writing	—	1671
LMArena Multi-Turn	—	1441

Frequently asked questions

Is Phi-4 Mini better than Qwen3.8 27B?

Which is cheaper, Phi-4 Mini or Qwen3.8 27B?

Phi-4 Mini is cheaper. It lists at $0.075 per million input tokens and $0.30 per million output tokens; Qwen3.8 27B lists at $0.04 and $2.30.

Is Phi-4 Mini or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 28.1 in the Noometry coding category.

Which has the bigger context window?

Qwen3.8 27B does, with 262K tokens against 128K.

How many benchmarks do Phi-4 Mini and Qwen3.8 27B share?

2 benchmarks have published results for both models. Phi-4 Mini has 3 scored results on Noometry and Qwen3.8 27B has 31.