Gemma 3n 2B (free) vs Qwen3.5-235B-A22B
Gemma 3n 2B (free) (2025) and Qwen3.5-235B-A22B (2026) are compact production models from Google DeepMind and Alibaba. Gemma 3n 2B (free) ships a 8K-token context window, while Qwen3.5-235B-A22B ships a 512k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
Qwen3.5-235B-A22B fits 64x more tokens; pick it for long-context work and Gemma 3n 2B (free) for tighter calls.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-03 | 2026-02-24 |
| Context window | 8K | 512k |
| Parameters | — | 235B |
| Architecture | decoder only | MoE |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Gemma 3n 2B (free) | Qwen3.5-235B-A22B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Gemma 3n 2B (free) | Qwen3.5-235B-A22B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
Pricing coverage is uneven: Gemma 3n 2B (free) has no token price sourced yet and Qwen3.5-235B-A22B has no token price sourced yet. Provider availability is 1 tracked routes versus 0. 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 and broader provider choice are central to the workload. Choose Qwen3.5-235B-A22B when long-context analysis and larger context windows 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 Qwen3.5-235B-A22B?
Qwen3.5-235B-A22B supports 512k 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 Qwen3.5-235B-A22B open source?
Gemma 3n 2B (free) is listed under Open Source. Qwen3.5-235B-A22B 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.
Where can I run Gemma 3n 2B (free) and Qwen3.5-235B-A22B?
Gemma 3n 2B (free) is available on NVIDIA NIM. Qwen3.5-235B-A22B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3n 2B (free) over Qwen3.5-235B-A22B?
Qwen3.5-235B-A22B fits 64x 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 Qwen3.5-235B-A22B.
Continue comparing
Last reviewed: 2026-05-01. Data sourced from public model cards and provider documentation.