LLM Reference

Gemma 3n 2B (free) vs Qwen2-72B

Gemma 3n 2B (free) (2025) and Qwen2-72B (2024) are compact production models from Google DeepMind and Alibaba. Gemma 3n 2B (free) ships a 8k-token context window, while Qwen2-72B ships 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.

Qwen2-72B fits 16x more tokens; pick it for long-context work and Gemma 3n 2B (free) for tighter calls.

Decision scorecard

Local evidence first
SignalGemma 3n 2B (free)Qwen2-72B
Best forgeneral production evaluationprovider-routed production
Decision fitGeneralCoding, RAG, and Long context
Context window8k128k
Cheapest output-$0.65/1M tokens
Provider routes1 tracked4 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Gemma 3n 2B (free) when...
  • Use Gemma 3n 2B (free) when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Choose Qwen2-72B when...
  • Qwen2-72B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen2-72B has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen2-72B uniquely exposes Structured outputs in local model data.
  • Local decision data tags Qwen2-72B for Coding, RAG, and Long context.

Monthly cost at traffic

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

Gemma 3n 2B (free)

Unavailable

No complete token price in local provider data

Qwen2-72B

$523

Cheapest tracked route/tier: DeepInfra

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

Switch friction

Gemma 3n 2B (free) -> Qwen2-72B
  • No overlapping tracked provider route is sourced for Gemma 3n 2B (free) and Qwen2-72B; plan for SDK, billing, or endpoint changes.
  • Qwen2-72B adds Structured outputs in local capability data.
Qwen2-72B -> Gemma 3n 2B (free)
  • No overlapping tracked provider route is sourced for Qwen2-72B and Gemma 3n 2B (free); plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2025-04-032024-06-05
Context window8k128k
Parameters5B (2B effective active)72.71B
ArchitectureDecoder OnlyDecoder Only
LicenseGemmaApache 2.0OSI-approved
OpennessOpen weightsOpen source
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff2024-06-

Pricing and availability

Pricing attributeGemma 3n 2B (free)Qwen2-72B
Input price-$0.45/1M tokens
Output price-$0.65/1M tokens
Providers

Capabilities

CapabilityGemma 3n 2B (free)Qwen2-72B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on structured outputs: Qwen2-72B. 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 3n 2B (free) has no token price sourced yet and Qwen2-72B has $0.45/1M input tokens. Provider availability is 1 tracked routes versus 4. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Gemma 3n 2B (free) when provider fit are central to the workload. Choose Qwen2-72B when long-context analysis, larger context windows, and broader provider choice 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 3n 2B (free) or Qwen2-72B?

Qwen2-72B supports 128k tokens, while Gemma 3n 2B (free) supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Gemma 3n 2B (free) or Qwen2-72B open source?

Gemma 3n 2B (free) is listed under Gemma. Qwen2-72B is listed under Apache 2.0. 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, Gemma 3n 2B (free) or Qwen2-72B?

Qwen2-72B 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 3n 2B (free) and Qwen2-72B?

Gemma 3n 2B (free) is available on NVIDIA NIM. Qwen2-72B is available on Fireworks AI, DeepInfra, Together AI, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Gemma 3n 2B (free) over Qwen2-72B?

Qwen2-72B fits 16x more tokens; pick it for long-context work and Gemma 3n 2B (free) for tighter calls. If your workload also depends on provider fit, start with Gemma 3n 2B (free); if it depends on long-context analysis, run the same evaluation with Qwen2-72B.

Continue comparing

Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.