vs
4:3
overall capability wins (1 ties across 8 scored). Phi-4-mini leads overall.
- Reasoning3:1
- Coding0:2
- Pricing3:0
- Speed2:0
- Specs1:0
Verdict
Phi-4-multimodal leads coding (widest gap: +0.5 on LiveCode); Phi-4-mini edges reasoning & knowledge; Phi-4-mini allows ~4.0x more max output (16K vs 4K).
- Phi-4-multimodal leads coding (widest gap: +0.5 on LiveCode)
- Phi-4-mini edges reasoning & knowledge
- Phi-4-mini allows ~4.0x more max output (16K vs 4K)
Cost for 1M in + 250K out
Illustrative chat workload at primary-provider list prices.
- Phi-4-mini
- $0.15
- Phi-4-multimodal
- $0.16
Phi-4-mini is about 1.1x cheaper on this workload.
Price per 1M tokens
Full comparison
Organization
Microsoft
Microsoft
Family
Phi
Phi
License
MIT
MIT
Open weights
Yes
Yes
Release
Feb 1, 2025
Feb 1, 2025
Knowledge cutoff
-
-
API / provider
Azure AI Foundry
Azure AI Foundry
Modalities
text → text
text, image, audio → text
Specs
Context window
131K
131K
Max output
16K
4K
Parameters
3.8B
—
Pricing
Input $/1M
$0.07
$0.08
Output $/1M
$0.30
$0.32
Blended $/1M (3∶1)
$0.13
$0.14
Speed
tok/s
140
90
TTFT (s)
0.18
0.35
Reasoning
MMLU-Pro
52.8
48.5
GPQA Diamond
33.1
31.5
Humanity's Last Exam
4.5
5.0
AIME 2025
6.7
—
MATH-500
69.6
69.3
Humanity's Last Exam (with tools)
—
—
AA-Omniscience Accuracy
9.5
—
AA-LCR v1.1
15.3
—
CritPt
—
—
MMMU-Pro
—
14.5
IFBench
21.1
—
Chartography
—
—
Chartography (With Tools)
—
—
Coding
SWE-bench Verified
—
—
SWE-bench Pro
—
—
SWE-bench Multilingual
—
—
LiveCodeBench
12.6
13.1
Terminal-Bench 2.1
0.4
—
Aider Polyglot
—
—
Terminal-Bench 3
—
—
BigCodeBench
—
—
SciCode
10.8
11.0
CursorBench
—
—
SWE-Rebench
—
—
NL2Repo-Bench
—
—
DeepSWE
—
—
WebDev Arena
—
—
Terminal-Bench 4.0
—
—
CursorBench 4.0
—
—
FrontierCode v1.1 (Main)
—
—
Arena
LMArena Elo
—
—
| Metric | Phi-4-mini | Phi-4-multimodal | Delta |
|---|---|---|---|
| Identity | |||
| Organization | Microsoft | Microsoft | — |
| Family | Phi | Phi | — |
| License | MIT | MIT | — |
| Open weights | Yes | Yes | — |
| Release | Feb 1, 2025 | Feb 1, 2025 | — |
| Knowledge cutoff | - | - | — |
| API / provider | Azure AI Foundry | Azure AI Foundry | — |
| Modalities | text → text | text, image, audio → text | — |
| Specs | |||
| Context window | 131K | 131K | tie |
| Max output | 16K | 4K | A +12K |
| Parameters | 3.8B | — | — |
| Pricing | |||
| Input $/1M | $0.07 | $0.08 | A +$0.005 |
| Output $/1M | $0.30 | $0.32 | A +$0.02 |
| Blended $/1M (3∶1) | $0.13 | $0.14 | A +$0.009 |
| Speed | |||
| tok/s | 140 | 90 | A +50 |
| TTFT (s) | 0.18 | 0.35 | A +0.17 |
| Reasoning | |||
| MMLU-Pro | 52.8 | 48.5 | A +4.3 pts |
| GPQA Diamond | 33.1 | 31.5 | A +1.6 pts |
| Humanity's Last Exam | 4.5 | 5.0 | B +0.5 pts |
| AIME 2025 | 6.7 | — | — |
| MATH-500 | 69.6 | 69.3 | A +0.3 pts |
| Humanity's Last Exam (with tools) | — | — | — |
| AA-Omniscience Accuracy | 9.5 | — | — |
| AA-LCR v1.1 | 15.3 | — | — |
| CritPt | — | — | — |
| MMMU-Pro | — | 14.5 | — |
| IFBench | 21.1 | — | — |
| Chartography | — | — | — |
| Chartography (With Tools) | — | — | — |
| Coding | |||
| SWE-bench Verified | — | — | — |
| SWE-bench Pro | — | — | — |
| SWE-bench Multilingual | — | — | — |
| LiveCodeBench | 12.6 | 13.1 | B +0.5 pts |
| Terminal-Bench 2.1 | 0.4 | — | — |
| Aider Polyglot | — | — | — |
| Terminal-Bench 3 | — | — | — |
| BigCodeBench | — | — | — |
| SciCode | 10.8 | 11.0 | B +0.2 pts |
| CursorBench | — | — | — |
| SWE-Rebench | — | — | — |
| NL2Repo-Bench | — | — | — |
| DeepSWE | — | — | — |
| WebDev Arena | — | — | — |
| Terminal-Bench 4.0 | — | — | — |
| CursorBench 4.0 | — | — | — |
| FrontierCode v1.1 (Main) | — | — | — |
| Arena | |||
| LMArena Elo | — | — | — |
Phi-4-mini
- Context
- 131K / 16K out
- Parameters
- 3.8B
- Price
- $0.07 / $0.30
- Speed
- 140 tok/s · 0.18s TTFT
- Modalities
- text → text
- License
- MIT
Next-gen Microsoft SLM with grouped-query attention and built-in function calling — strong edge and mobile deployment choice.
Phi-4-multimodal
- Context
- 131K / 4K out
- Parameters
- —
- Price
- $0.08 / $0.32
- Speed
- 90 tok/s · 0.35s TTFT
- Modalities
- text, image, audio → text
- License
- MIT
First multimodal Phi — unified text, vision, and speech inputs for on-device assistants and accessibility apps.
Benchmark charts
Winner bars are emphasized. Per-benchmark deltas sit above each chart.