Which is cheaper, DeepSeek R1 or Phi-4?

Phi-4 is cheaper for both input ($0.07/M tokens) and output ($0.14/M tokens), compared to DeepSeek R1 at $0.55/$2.19 per million tokens.

Which is faster, DeepSeek R1 or Phi-4?

Phi-4 is faster at 160 tokens/sec with a TTFT of 100ms, compared to DeepSeek R1 at 45 tokens/sec and 1800ms TTFT.

Which has a bigger context window, DeepSeek R1 or Phi-4?

DeepSeek R1 has a 128K token context window, which is larger Phi-4's 16K context window.

Which is better for coding, DeepSeek R1 or Phi-4?

DeepSeek R1 has a higher coding ELO of 1330 compared to Phi-4's 1130, making it the stronger choice for code generation and programming tasks.

DeepSeek R1 vs Phi-4: Pricing, Benchmarks & Verdict (2026)

Verdict

Phi-4 is significantly cheaper at $0.07/$0.14 per million tokens vs $0.55/$2.19. DeepSeek R1 is stronger for coding with a coding ELO of 1330 vs 1130. Phi-4 is faster at 160 tokens/sec vs 45 tokens/sec. DeepSeek R1 ranks higher overall with an Arena ELO of 1310 vs 1150. DeepSeek R1 offers a larger 128K context window vs 16K.

Side-by-Side Comparison

Feature	DeepSeek R1	Phi-4
Provider	DeepSeek	Microsoft
Input Price / 1M tokens	$0.550	$0.070
Output Price / 1M tokens	$2.19	$0.140
Context Window	128K	16.384K
Max Output Tokens	8,192	4,096
Arena ELO	1,310	1,150
Coding ELO	1,330	1,130
TTFT (ms)	1,800	100
Tokens/sec	45	160
Multimodal	No	No
JSON Mode	Yes	Yes
Function Calling	No	No
Vision	No	No

When to Use DeepSeek R1

Choose DeepSeek R1 when you need: excellent reasoning at a fraction of o3's cost, open-source and self-hostable, top-tier math performance, very competitive with proprietary reasoning models. It excels at reasoning, math, coding, science tasks. Its 128K context window is larger, making it better for long-document processing.

Strengths:

Excellent reasoning at a fraction of o3's cost
Open-source and self-hostable
Top-tier math performance
Very competitive with proprietary reasoning models

Best for:

reasoningmathcodingscience

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

DeepSeek R1 vs Phi-4: Pricing, Benchmarks & Verdict (2026)

Side-by-Side Comparison

Frequently Asked Questions

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