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DeepSeek V3.2 vs Gemma 3 12B (free)

DeepSeek V3.2 (2025) and Gemma 3 12B (free) (2026) are compact production models from DeepSeek and Google DeepMind. DeepSeek V3.2 ships a 160K-token context window, while Gemma 3 12B (free) ships a 33K-token context window. On pricing, Gemma 3 12B (free) costs $0.04/1M input tokens versus $0.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Gemma 3 12B (free) is ~530% cheaper at $0.04/1M; pay for DeepSeek V3.2 only for coding workflow support.

Specs

Specification
Released2025-01-012026-01-01
Context window160K33K
Parameters671B
Architecturedecoder onlydecoder only
LicenseOpen SourceOpen Source
Knowledge cutoff--

Pricing and availability

Pricing attributeDeepSeek V3.2Gemma 3 12B (free)
Input price$0.25/1M tokens$0.04/1M tokens
Output price$0.38/1M tokens$0.13/1M tokens
Providers

Capabilities

CapabilityDeepSeek V3.2Gemma 3 12B (free)
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsYesYes
Code executionYesNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on code execution: DeepSeek V3.2. Both models share structured outputs, 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.

For cost, DeepSeek V3.2 lists $0.25/1M input and $0.38/1M output tokens, while Gemma 3 12B (free) lists $0.04/1M input and $0.13/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 3 12B (free) lower by about $0.22 per million blended tokens. Availability is 4 providers versus 3, so concentration risk also matters.

Choose DeepSeek V3.2 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Gemma 3 12B (free) when provider fit and lower input-token cost 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.

FAQ

Which has a larger context window, DeepSeek V3.2 or Gemma 3 12B (free)?

DeepSeek V3.2 supports 160K tokens, while Gemma 3 12B (free) supports 33K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, DeepSeek V3.2 or Gemma 3 12B (free)?

Gemma 3 12B (free) is cheaper on tracked token pricing. DeepSeek V3.2 costs $0.25/1M input and $0.38/1M output tokens. Gemma 3 12B (free) costs $0.04/1M input and $0.13/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is DeepSeek V3.2 or Gemma 3 12B (free) open source?

DeepSeek V3.2 is listed under Open Source. Gemma 3 12B (free) is listed under Open Source. 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 structured outputs, DeepSeek V3.2 or Gemma 3 12B (free)?

Both DeepSeek V3.2 and Gemma 3 12B (free) expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for code execution, DeepSeek V3.2 or Gemma 3 12B (free)?

DeepSeek V3.2 has the clearer documented code execution signal in this comparison. If code execution is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run DeepSeek V3.2 and Gemma 3 12B (free)?

DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. Gemma 3 12B (free) is available on AWS Bedrock, OpenRouter, and GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.