Gemma 3n 2B (free) vs Phi 4 Multimodal Instruct
Gemma 3n 2B (free) (2025) and Phi 4 Multimodal Instruct (2025) are compact production models from Google DeepMind and Microsoft Research. Gemma 3n 2B (free) ships a 8k-token context window, while Phi 4 Multimodal Instruct 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.
Phi 4 Multimodal Instruct fits 16x more tokens; pick it for long-context work and Gemma 3n 2B (free) for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemma 3n 2B (free) | Phi 4 Multimodal Instruct |
|---|---|---|
| Best for | general production evaluation | multimodal apps and provider-routed production |
| Decision fit | General | Long context and Vision |
| Context window | 8k | 128k |
| Cheapest output | - | $0.90/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- 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.
- Phi 4 Multimodal Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Phi 4 Multimodal Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Phi 4 Multimodal Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Phi 4 Multimodal Instruct for Long context and Vision.
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
Phi 4 Multimodal Instruct
$945
Cheapest tracked route/tier: Fireworks AI
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Phi 4 Multimodal Instruct adds Vision and Multimodal in local capability data.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
Pricing and availability
| Pricing attribute | Gemma 3n 2B (free) | Phi 4 Multimodal Instruct |
|---|---|---|
| Input price | - | $0.90/1M tokens |
| Output price | - | $0.90/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3n 2B (free) | Phi 4 Multimodal Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | 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 vision: Phi 4 Multimodal Instruct and multimodal input: Phi 4 Multimodal Instruct. 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 Phi 4 Multimodal Instruct has $0.90/1M input tokens. Provider availability is 1 tracked routes versus 3. 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 Phi 4 Multimodal Instruct 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.
FAQ
Which has a larger context window, Gemma 3n 2B (free) or Phi 4 Multimodal Instruct?
Phi 4 Multimodal Instruct 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 Phi 4 Multimodal Instruct open source?
Gemma 3n 2B (free) is listed under Gemma. Phi 4 Multimodal Instruct 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 vision, Gemma 3n 2B (free) or Phi 4 Multimodal Instruct?
Phi 4 Multimodal Instruct has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Gemma 3n 2B (free) or Phi 4 Multimodal Instruct?
Phi 4 Multimodal Instruct has the clearer documented multimodal input signal in this comparison. If multimodal input 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 Phi 4 Multimodal Instruct?
Gemma 3n 2B (free) is available on NVIDIA NIM. Phi 4 Multimodal Instruct is available on Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3n 2B (free) over Phi 4 Multimodal Instruct?
Phi 4 Multimodal Instruct 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 Phi 4 Multimodal Instruct.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.