Gemma 3n 4B (free) vs Trinity-Large-Thinking
Gemma 3n 4B (free) (2025) and Trinity-Large-Thinking (2026) are frontier reasoning models from Google DeepMind and Arcee AI. Gemma 3n 4B (free) ships a 8K-token context window, while Trinity-Large-Thinking ships a 256K-token context window. On pricing, Gemma 3n 4B (free) costs $0.02/1M input tokens versus $0.22/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemma 3n 4B (free) is ~1000% cheaper at $0.02/1M; pay for Trinity-Large-Thinking only for reasoning depth.
Decision scorecard
Local evidence first| Signal | Gemma 3n 4B (free) | Trinity-Large-Thinking |
|---|---|---|
| Best for | provider-routed production | reasoning-heavy apps, tool-calling agents, and provider-routed production |
| Decision fit | Classification and JSON / Tool use | RAG, Agents, and Long context |
| Context window | 8K | 256K |
| Cheapest output | $0.04/1M tokens | $0.85/1M tokens |
| Provider routes | 3 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3n 4B (free) has the lower cheapest tracked output price at $0.04/1M tokens.
- Local decision data tags Gemma 3n 4B (free) for Classification and JSON / Tool use.
- Trinity-Large-Thinking has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Trinity-Large-Thinking uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags Trinity-Large-Thinking for RAG, Agents, 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 4B (free)
$26.00
Cheapest tracked route/tier: Together AI
Trinity-Large-Thinking
$389
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $363. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Trinity-Large-Thinking is $0.81/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Trinity-Large-Thinking adds Reasoning, Function calling, and Tool use in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Gemma 3n 4B (free) is $0.81/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-03 | 2026-04-01 |
| Context window | 8K | 256K |
| Parameters | 8B (4B effective active) | 400B |
| Architecture | decoder only | Sparse Mixture of Experts (MoE) |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Gemma 3n 4B (free) | Trinity-Large-Thinking |
|---|---|---|
| Input price | $0.02/1M tokens | $0.22/1M tokens |
| Output price | $0.04/1M tokens | $0.85/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3n 4B (free) | Trinity-Large-Thinking |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Trinity-Large-Thinking, function calling: Trinity-Large-Thinking, and tool use: Trinity-Large-Thinking. 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, Gemma 3n 4B (free) lists $0.02/1M input and $0.04/1M output tokens on the cheapest tracked provider, while Trinity-Large-Thinking lists $0.22/1M input and $0.85/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 3n 4B (free) lower by about $0.38 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.
Choose Gemma 3n 4B (free) when provider fit and lower input-token cost are central to the workload. Choose Trinity-Large-Thinking when reasoning depth 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.
FAQ
Which has a larger context window, Gemma 3n 4B (free) or Trinity-Large-Thinking?
Trinity-Large-Thinking supports 256K tokens, while Gemma 3n 4B (free) supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemma 3n 4B (free) or Trinity-Large-Thinking?
Gemma 3n 4B (free) is cheaper on tracked token pricing. Gemma 3n 4B (free) costs $0.02/1M input and $0.04/1M output tokens. Trinity-Large-Thinking costs $0.22/1M input and $0.85/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 3n 4B (free) or Trinity-Large-Thinking open source?
Gemma 3n 4B (free) is listed under Proprietary. Trinity-Large-Thinking 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 reasoning mode, Gemma 3n 4B (free) or Trinity-Large-Thinking?
Trinity-Large-Thinking 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 function calling, Gemma 3n 4B (free) or Trinity-Large-Thinking?
Trinity-Large-Thinking has the clearer documented function calling signal in this comparison. If function calling 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 4B (free) and Trinity-Large-Thinking?
Gemma 3n 4B (free) is available on NVIDIA NIM, Together AI, and OpenRouter. Trinity-Large-Thinking is available on Arcee AI, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.