Phi-3 Mini 128K vs Qwen3.5-397B-A17B
Phi-3 Mini 128K (2024) and Qwen3.5-397B-A17B (2026) are frontier reasoning models from Microsoft Research and Alibaba. Phi-3 Mini 128K ships a 128k-token context window, while Qwen3.5-397B-A17B ships a 262k-token context window. On MMLU PRO, Qwen3.5-397B-A17B leads by 43.9 pts. On pricing, Phi-3 Mini 128K costs $0.05/1M input tokens versus $0.39/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Phi-3 Mini 128K is ~680% cheaper at $0.05/1M; pay for Qwen3.5-397B-A17B only for reasoning depth.
Decision scorecard
Local evidence first| Signal | Phi-3 Mini 128K | Qwen3.5-397B-A17B |
|---|---|---|
| Best for | provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, Long context, and Classification | Coding, RAG, and Agents |
| Context window | 128k | 262k |
| Cheapest output | $0.25/1M tokens | $2.34/1M tokens |
| Provider routes | 5 tracked | 4 tracked |
| Shared benchmarks | 2 shared | MMLU PRO leader |
Decision tradeoffs
- Phi-3 Mini 128K has the lower cheapest tracked output price at $0.25/1M tokens.
- Phi-3 Mini 128K has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Phi-3 Mini 128K for Coding, Long context, and Classification.
- Qwen3.5-397B-A17B holds a shared-benchmark lead on MMLU PRO, ahead by 43.9 points.
- Qwen3.5-397B-A17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-397B-A17B uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Qwen3.5-397B-A17B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Phi-3 Mini 128K
$103
Cheapest tracked route/tier: Replicate API
Qwen3.5-397B-A17B
$897
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $795. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Phi-3 Mini 128K and Qwen3.5-397B-A17B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-397B-A17B is $2.09/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.5-397B-A17B adds Vision, Multimodal, and Reasoning in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-397B-A17B and Phi-3 Mini 128K; plan for SDK, billing, or endpoint changes.
- Phi-3 Mini 128K is $2.09/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-23 | 2026-02-16 |
| Context window | 128k | 262k |
| Parameters | 3.8B | 397B |
| Architecture | Decoder Only | Mixture of Experts |
| License | MITOSI-approved | Apache 2.0OSI-approved |
| Openness | Open source | Open source |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | 2023-10 | - |
Pricing and availability
| Pricing attribute | Phi-3 Mini 128K | Qwen3.5-397B-A17B |
|---|---|---|
| Input price | $0.05/1M tokens | $0.39/1M tokens |
| Output price | $0.25/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Capability | Phi-3 Mini 128K | Qwen3.5-397B-A17B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | No | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Phi-3 Mini 128K | Qwen3.5-397B-A17B |
|---|---|---|
| MMLU PRO | 43.9 | 87.8 |
| Google-Proof Q&A | 50.8 | 89.3 |
Deep dive
On shared benchmark coverage, MMLU PRO has Phi-3 Mini 128K at 43.9 and Qwen3.5-397B-A17B at 87.8, with Qwen3.5-397B-A17B ahead by 43.9 points; Google-Proof Q&A has Phi-3 Mini 128K at 50.8 and Qwen3.5-397B-A17B at 89.3, with Qwen3.5-397B-A17B ahead by 38.5 points. The largest visible gap is 43.9 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Qwen3.5-397B-A17B, multimodal input: Qwen3.5-397B-A17B, reasoning mode: Qwen3.5-397B-A17B, function calling: Qwen3.5-397B-A17B, tool use: Qwen3.5-397B-A17B, and structured outputs: Qwen3.5-397B-A17B. 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.
For cost, Phi-3 Mini 128K lists $0.05/1M input and $0.25/1M output tokens on the cheapest tracked provider, while Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-3 Mini 128K lower by about $0.86 per million blended tokens. Availability is 5 providers versus 4, so concentration risk also matters.
Choose Phi-3 Mini 128K when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3.5-397B-A17B 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.
FAQ
Which has a larger context window, Phi-3 Mini 128K or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B supports 262k tokens, while Phi-3 Mini 128K supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Phi-3 Mini 128K or Qwen3.5-397B-A17B?
Phi-3 Mini 128K is cheaper on tracked token pricing. Phi-3 Mini 128K costs $0.05/1M input and $0.25/1M output tokens. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Phi-3 Mini 128K or Qwen3.5-397B-A17B open source?
Phi-3 Mini 128K is listed under MIT. Qwen3.5-397B-A17B 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 vision, Phi-3 Mini 128K or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Phi-3 Mini 128K or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B 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 Phi-3 Mini 128K and Qwen3.5-397B-A17B?
Phi-3 Mini 128K is available on NVIDIA NIM, Baseten API, Microsoft Foundry, Fireworks AI, and Replicate API. Qwen3.5-397B-A17B is available on OpenRouter, Together AI, Alibaba Cloud PAI-EAS, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.