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Google: Gemma 3 27B vs Microsoft: Phi 4

Neither wins outright: Google: Gemma 3 27B is the pick when you need to fit long inputs in one request, Microsoft: Phi 4 when cost matters at scale.

Key numbers

SpecGoogle: Gemma 3 27BMicrosoft: Phi 4
ProviderGoogleMicrosoft
Input price (per 1M tokens)$0.08$0.07
Output price (per 1M tokens)$0.35$0.14
Blended price (3:1 input/output)$0.15$0.09
Cheaper than … of all models we track75%82%
Context window131K tokens (~197 pages)16K tokens (~25 pages)
Larger context than … of all models22%4%
Max output per response118K tokens (~88,500 words)15K tokens (~11,100 words)
Input typestext, imagetext
Output typestexttext
Free variantYesNo
Listed since2025-03-122025-01-10
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What it costs for real workloads

Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.

Workload (per month)Google: Gemma 3 27BMicrosoft: Phi 4Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$13.00$8.05Microsoft: Phi 4 saves $4.95
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$13.10$9.80Microsoft: Phi 4 saves $3.30
Coding / tool-using agent
2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens)
$13.80Doesn't fit context—
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$8.50$6.44Microsoft: Phi 4 saves $2.06
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$4.35Doesn't fit context—

Capabilities side by side

CapabilityGoogle: Gemma 3 27BMicrosoft: Phi 4What it lets you do
Tool / function calling✓ Yes—call your APIs and run agent loops
Structured output (JSON schema)✓ Yes✓ Yesreturn JSON that validates against your schema
Reasoning / thinking mode——spend extra tokens thinking before answering hard problems
Image input✓ Yes—read screenshots, charts and scanned pages
Audio input——take speech or audio directly
File / PDF input——accept documents without your own parsing step
Image output——generate images, not just text
Built-in web search——answer from live web results
Seed (reproducible sampling)✓ Yes✓ Yesrepeat a generation for tests and evals
Log-probabilities✓ Yes—read token confidence for classification and scoring

From each model's published parameters and input/output types. “—” means not advertised, not proven absent.

Price history

DateModelInput / 1MOutput / 1M
2026-10-18Google: Gemma 3 27B$0.08$0.35
2026-08-06Google: Gemma 3 27B$0.08$0.45
2026-08-06Microsoft: Phi 4$0.07$0.14
2026-03-31Google: Gemma 3 27B$0.08$0.16
2026-03-31Microsoft: Phi 4$0.07$0.14

Which should you choose?

Choose Google: Gemma 3 27B if…

  • you need to fit long inputs in one request — 131K tokens is roughly 197 pages, against 25
  • you need tool / function calling — to call your APIs and run agent loops; Microsoft: Phi 4 does not advertise it
  • you need image input — to read screenshots, charts and scanned pages; Microsoft: Phi 4 does not advertise it
  • you need log-probabilities — to read token confidence for classification and scoring; Microsoft: Phi 4 does not advertise it
  • you generate long outputs in one go — up to 118K tokens (about 88,500 words) per response
  • you want to prototype at zero cost — a free variant is listed

Choose Microsoft: Phi 4 if…

  • cost matters at scale — it is 41% cheaper on a typical 3:1 input/output mix ($8.05 vs $13.00 a month for 50,000 support chats)

Frequently asked questions

Is Google: Gemma 3 27B better than Microsoft: Phi 4?

Neither wins outright: Google: Gemma 3 27B is the pick when you need to fit long inputs in one request, Microsoft: Phi 4 when cost matters at scale. In short: Google: Gemma 3 27B when you need to fit long inputs in one request, you need tool / function calling, you need image input, you need log-probabilities, you generate long outputs in one go, you want to prototype at zero cost; Microsoft: Phi 4 when cost matters at scale.

Which is cheaper, Google: Gemma 3 27B or Microsoft: Phi 4?

Microsoft: Phi 4 is cheaper: $0.09 vs $0.15 per 1M tokens at a typical 3:1 input/output mix, 41% less. For 50,000 support conversations a month that is $8.05 against $13.00.

How much do Google: Gemma 3 27B and Microsoft: Phi 4 cost per million tokens?

Google: Gemma 3 27B costs $0.08 per 1M input tokens and $0.35 per 1M output tokens; Microsoft: Phi 4 costs $0.07 input and $0.14 output. Output tokens are billed separately, so long answers shift the gap.

Which has the bigger context window, Google: Gemma 3 27B or Microsoft: Phi 4?

Google: Gemma 3 27B: 131K tokens, about 197 pages, against 16K (about 25 pages) for Microsoft: Phi 4.

Do Google: Gemma 3 27B and Microsoft: Phi 4 support function calling and JSON output?

Tool calling — Google: Gemma 3 27B: yes, Microsoft: Phi 4: not advertised. JSON-schema structured output — Google: Gemma 3 27B: yes, Microsoft: Phi 4: yes.

Can Google: Gemma 3 27B or Microsoft: Phi 4 read images?

Only Google: Gemma 3 27B accepts image input; Microsoft: Phi 4 is text-only for input.

Is Google: Gemma 3 27B or Microsoft: Phi 4 free to use?

Google: Gemma 3 27B has a free variant (google/gemma-3-27b-it:free). Free variants usually carry tighter rate limits.

What is the maximum output length of Google: Gemma 3 27B and Microsoft: Phi 4?

Google: Gemma 3 27B can write up to 118K tokens (about 88,500 words) per response; Microsoft: Phi 4 up to 15K (about 11,100 words).

When were Google: Gemma 3 27B and Microsoft: Phi 4 released?

Google: Gemma 3 27B was listed on 2025-03-12; Microsoft: Phi 4 on 2025-01-10.

Has the price of Google: Gemma 3 27B or Microsoft: Phi 4 changed?

Google: Gemma 3 27B: output price cut 22% ($0.45 → $0.35/1M) on 2026-10-18 (3 price changes since 2026-03-10). Microsoft: Phi 4: input price raised 7% ($0.07 → $0.07/1M) on 2026-08-06 (2 price changes since 2026-03-10).

About the two models

Google

Google: Gemma 3 27B

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

Full Google: Gemma 3 27B specs →
Microsoft

Microsoft: Phi 4

[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...

Full Microsoft: Phi 4 specs →

Compare Google: Gemma 3 27B with other models

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Compare Microsoft: Phi 4 with other models

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