Which is cheaper, Gemini 2.5 Pro or Phi-4?

Phi-4 is cheaper for both input ($0.07/M tokens) and output ($0.14/M tokens), compared to Gemini 2.5 Pro at $1.25/$10.00 per million tokens.

Which is faster, Gemini 2.5 Pro or Phi-4?

Phi-4 is faster at 160 tokens/sec with a TTFT of 100ms, compared to Gemini 2.5 Pro at 70 tokens/sec and 400ms TTFT.

Which has a bigger context window, Gemini 2.5 Pro or Phi-4?

Gemini 2.5 Pro has a 1049K token context window, which is larger Phi-4's 16K context window.

Which is better for coding, Gemini 2.5 Pro or Phi-4?

Gemini 2.5 Pro has a higher coding ELO of 1350 compared to Phi-4's 1130, making it the stronger choice for code generation and programming tasks.

Gemini 2.5 Pro vs Phi-4: Pricing, Benchmarks & Verdict (2026)

Verdict

Phi-4 is significantly cheaper at $0.07/$0.14 per million tokens vs $1.25/$10.00. Gemini 2.5 Pro is stronger for coding with a coding ELO of 1350 vs 1130. Phi-4 is faster at 160 tokens/sec vs 70 tokens/sec. Gemini 2.5 Pro ranks higher overall with an Arena ELO of 1340 vs 1150. Gemini 2.5 Pro offers a larger 1049K context window vs 16K.

Side-by-Side Comparison

Feature	Gemini 2.5 Pro	Phi-4
Provider	Google	Microsoft
Input Price / 1M tokens	$1.25	$0.070
Output Price / 1M tokens	$10.00	$0.140
Context Window	1.048576M	16.384K
Max Output Tokens	65,536	4,096
Arena ELO	1,340	1,150
Coding ELO	1,350	1,130
TTFT (ms)	400	100
Tokens/sec	70	160
Multimodal	Yes	No
JSON Mode	Yes	Yes
Function Calling	Yes	No
Vision	Yes	No

When to Use Gemini 2.5 Pro

Choose Gemini 2.5 Pro when you need: 1m token context window, excellent reasoning capabilities, strong coding performance, native multimodal support. It excels at coding, reasoning, long-context, multimodal tasks. Its 1049K context window is larger, making it better for long-document processing.

Strengths:

1M token context window
Excellent reasoning capabilities
Strong coding performance
Native multimodal support

Best for:

codingreasoninglong-contextmultimodal

When to Use Phi-4

Choose Phi-4 when you need: ultra-low cost for a capable model, strong math for its size (14b params), very fast inference, can run on consumer hardware. It excels at cost-sensitive, edge-deployment, math, lightweight-tasks tasks. It is also the more cost-effective option between the two.

Strengths:

Ultra-low cost for a capable model
Strong math for its size (14B params)
Very fast inference
Can run on consumer hardware

Best for:

cost-sensitiveedge-deploymentmathlightweight-tasks

Gemini 2.5 Pro vs Phi-4: Pricing, Benchmarks & Verdict (2026)

Side-by-Side Comparison

Frequently Asked Questions

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