Gemma 3 12B vs Phi-4 Mini Flash Reasoning

Name: Gemma 3 12B
Author: Google DeepMind

Gemma 3 12B (2025) and Phi-4 Mini Flash Reasoning (2025) are frontier reasoning models from Google DeepMind and Microsoft Research. Both ship a 128K-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Phi-4 Mini Flash Reasoning is safer overall; choose Gemma 3 12B when provider fit matters.

Decision scorecard

Local evidence first

Signal	Gemma 3 12B	Phi-4 Mini Flash Reasoning	How to read it
Best for	provider-routed production	reasoning-heavy apps	Use-case synthesis from product type, capability flags, context, and provider data.
Decision fit	RAG, Long context, and Classification	Long context	Primary workload tags from local decision data.
Context window	128K	128K	Higher is better when prompts, retrieval chunks, or transcripts are large.
Cheapest output	$0.13/1M tokens	-	Cheapest tracked provider route; verify your exact region and tier.
Provider routes	6 tracked	1 tracked	Broader coverage can reduce vendor lock-in and fallback risk.
Shared benchmarks	0 shared	0 shared	No shared benchmark scores are available for this pair yet.

Decision tradeoffs

Choose Gemma 3 12B when...

Gemma 3 12B has broader tracked provider coverage for fallback and route flexibility.
Gemma 3 12B uniquely exposes Structured outputs in local model data.
Local decision data tags Gemma 3 12B for RAG, Long context, and Classification.

Choose Phi-4 Mini Flash Reasoning when...

Phi-4 Mini Flash Reasoning uniquely exposes Reasoning in local model data.
Local decision data tags Phi-4 Mini Flash Reasoning for Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Requests / monthInput tokens / requestOutput tokens / request

Gemma 3 12B

$64.50

Cheapest tracked route/tier: GCP Vertex AI

Phi-4 Mini Flash Reasoning

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Gemma 3 12B -> Phi-4 Mini Flash Reasoning

No overlapping tracked provider route is sourced for Gemma 3 12B and Phi-4 Mini Flash Reasoning; plan for SDK, billing, or endpoint changes.
Check replacement coverage for Structured outputs before moving production traffic.
Phi-4 Mini Flash Reasoning adds Reasoning in local capability data.

Phi-4 Mini Flash Reasoning -> Gemma 3 12B

No overlapping tracked provider route is sourced for Phi-4 Mini Flash Reasoning and Gemma 3 12B; plan for SDK, billing, or endpoint changes.
Check replacement coverage for Reasoning before moving production traffic.
Gemma 3 12B adds Structured outputs in local capability data.

Specs

Specification	Gemma 3 12B Google DeepMind	Phi-4 Mini Flash Reasoning Microsoft Research
Released	2025-03-12	2025-12-01
Context window	128K	128K
Parameters	12B	3.8B
Architecture	Decoder Only	Decoder Only
License	Gemma	MITOSI-approved
Openness	Open weights	Open source
Weights	Available	Unknown
Code	Unknown	Unknown
Commercial use	Restricted	Permitted
Knowledge cutoff	2024-08	2025-02

Pricing and availability

Pricing attribute	Gemma 3 12B	Phi-4 Mini Flash Reasoning
Input price	$0.04/1M tokens	-
Output price	$0.13/1M tokens	-
Providers	Cloudflare Workers AI Fireworks AI AWS Bedrock OpenRouter GCP Vertex AI Novita AI	NVIDIA NIM

Capabilities

Capability	Gemma 3 12B	Phi-4 Mini Flash Reasoning
Vision	No	No
Multimodal	No	No
Reasoning	No	Yes
JSON / Tool use	No	No
Structured outputs	Yes	No
Code execution	No	No
IDE integration	No	No
Computer use	No	No
Parallel agents	No	No

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on reasoning mode: Phi-4 Mini Flash Reasoning and structured outputs: Gemma 3 12B. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: Gemma 3 12B has $0.04/1M input tokens and Phi-4 Mini Flash Reasoning has no token price listed. Provider availability is 6 listed routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Gemma 3 12B when provider fit and broader provider choice are central to the workload. Choose Phi-4 Mini Flash Reasoning when reasoning depth are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, Gemma 3 12B or Phi-4 Mini Flash Reasoning?

Gemma 3 12B supports 128K tokens, while Phi-4 Mini Flash Reasoning supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Gemma 3 12B or Phi-4 Mini Flash Reasoning open source?

Gemma 3 12B is listed under Gemma. Phi-4 Mini Flash Reasoning is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for reasoning mode, Gemma 3 12B or Phi-4 Mini Flash Reasoning?

Phi-4 Mini Flash Reasoning has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Gemma 3 12B or Phi-4 Mini Flash Reasoning?

Gemma 3 12B has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Gemma 3 12B and Phi-4 Mini Flash Reasoning?

Gemma 3 12B is available on Cloudflare Workers AI, Fireworks AI, AWS Bedrock, OpenRouter, and GCP Vertex AI. Phi-4 Mini Flash Reasoning is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Gemma 3 12B over Phi-4 Mini Flash Reasoning?

Phi-4 Mini Flash Reasoning is safer overall; choose Gemma 3 12B when provider fit matters. If your workload also depends on provider fit, start with Gemma 3 12B; if it depends on reasoning depth, run the same evaluation with Phi-4 Mini Flash Reasoning.

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Last reviewed: 2026-10-26. Data sourced from public model cards and provider documentation.

Both models

Gemma 3 12B Phi-4 Mini Flash Reasoning