Phi-4 14B vs Qwen3.5-122B-A10B
Phi-4 14B (2024) and Qwen3.5-122B-A10B (2026) are frontier reasoning models from Microsoft Research and Alibaba. Phi-4 14B ships a 16k-token context window, while Qwen3.5-122B-A10B ships a 262k-token context window. On Google-Proof Q&A, Qwen3.5-122B-A10B leads by 29.6 pts. On pricing, Phi-4 14B costs $0.07/1M input tokens versus $0.26/1M 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-4 14B is ~300% cheaper at $0.07/1M; pay for Qwen3.5-122B-A10B only for reasoning depth.
Decision scorecard
Local evidence first| Signal | Phi-4 14B | Qwen3.5-122B-A10B |
|---|---|---|
| Best for | provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Classification and JSON / Tool use | Coding, RAG, and Agents |
| Context window | 16k | 262k |
| Cheapest output | $0.14/1M tokens | $2.08/1M tokens |
| Provider routes | 3 tracked | 3 tracked |
| Shared benchmarks | 1 rows | Google-Proof Q&A leader |
Decision tradeoffs
- Phi-4 14B has the lower cheapest tracked output price at $0.14/1M tokens.
- Local decision data tags Phi-4 14B for Classification and JSON / Tool use.
- Qwen3.5-122B-A10B holds a shared-benchmark lead on Google-Proof Q&A, ahead by 29.6 points.
- Qwen3.5-122B-A10B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-122B-A10B uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Qwen3.5-122B-A10B 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-4 14B
$87.00
Cheapest tracked route/tier: OpenRouter
Qwen3.5-122B-A10B
$728
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $641. 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.
- Qwen3.5-122B-A10B is $1.94/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.5-122B-A10B adds Vision, Multimodal, and Reasoning in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Phi-4 14B is $1.94/1M 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 | 2024-12-13 | 2026-02-24 |
| Context window | 16k | 262k |
| Parameters | 14B | 122B |
| Architecture | decoder only | mixture of experts |
| License | MIT(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Phi-4 14B | Qwen3.5-122B-A10B |
|---|---|---|
| Input price | $0.07/1M tokens | $0.26/1M tokens |
| Output price | $0.14/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | Phi-4 14B | Qwen3.5-122B-A10B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| 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
| Benchmark | Phi-4 14B | Qwen3.5-122B-A10B |
|---|---|---|
| Google-Proof Q&A | 56.1 | 85.7 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Phi-4 14B at 56.1 and Qwen3.5-122B-A10B at 85.7, with Qwen3.5-122B-A10B ahead by 29.6 points. The largest visible gap is 29.6 points on Google-Proof Q&A, 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: Qwen3.5-122B-A10B, multimodal input: Qwen3.5-122B-A10B, reasoning mode: Qwen3.5-122B-A10B, function calling: Qwen3.5-122B-A10B, and tool use: Qwen3.5-122B-A10B. 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, Phi-4 14B lists $0.07/1M input and $0.14/1M output tokens on the cheapest tracked provider, while Qwen3.5-122B-A10B lists $0.26/1M input and $2.08/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-4 14B lower by about $0.72 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.
Choose Phi-4 14B when provider fit and lower input-token cost are central to the workload. Choose Qwen3.5-122B-A10B 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-4 14B or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B supports 262k tokens, while Phi-4 14B supports 16k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, Phi-4 14B or Qwen3.5-122B-A10B?
Phi-4 14B is cheaper on tracked token pricing. Phi-4 14B costs $0.07/1M input and $0.14/1M output tokens. Qwen3.5-122B-A10B costs $0.26/1M input and $2.08/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Phi-4 14B or Qwen3.5-122B-A10B open source?
Phi-4 14B is listed under MIT. Qwen3.5-122B-A10B 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-4 14B or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B 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-4 14B or Qwen3.5-122B-A10B?
Qwen3.5-122B-A10B 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-4 14B and Qwen3.5-122B-A10B?
Phi-4 14B is available on OpenRouter, Fireworks AI, and Microsoft Foundry. Qwen3.5-122B-A10B is available on OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI. 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.