Phi 4 Multimodal Instruct vs Qwen1.5-110B
Phi 4 Multimodal Instruct (2025) and Qwen1.5-110B (2024) are compact production models from Microsoft Research and Alibaba. Phi 4 Multimodal Instruct ships a 128K-token context window, while Qwen1.5-110B ships a not-yet-sourced context window. On pricing, Phi 4 Multimodal Instruct costs $0.9/1M input tokens versus $1.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Phi 4 Multimodal Instruct is ~67% cheaper at $0.9/1M; pay for Qwen1.5-110B only for provider fit.
Decision scorecard
Local evidence first| Signal | Phi 4 Multimodal Instruct | Qwen1.5-110B |
|---|---|---|
| Decision fit | Long context and Vision | Coding, Classification, and JSON / Tool use |
| Context window | 128K | — |
| Cheapest output | $0.9/1M tokens | $2.5/1M tokens |
| Provider routes | 3 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Phi 4 Multimodal Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Phi 4 Multimodal Instruct has the lower cheapest tracked output price at $0.9/1M tokens.
- 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.
- Qwen1.5-110B uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen1.5-110B for Coding, Classification, and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Phi 4 Multimodal Instruct
$945
Cheapest tracked route: Fireworks AI
Qwen1.5-110B
$1,825
Cheapest tracked route: Microsoft Foundry
Estimated monthly gap: $880. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Microsoft Foundry; start route-level A/B tests there.
- Qwen1.5-110B is $1.6/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- Qwen1.5-110B adds Structured outputs in local capability data.
- Provider overlap exists on Microsoft Foundry; start route-level A/B tests there.
- Phi 4 Multimodal Instruct is $1.6/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
- Phi 4 Multimodal Instruct adds Vision and Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-01 | 2024-04-25 |
| Context window | 128K | — |
| Parameters | — | 110B |
| Architecture | decoder only | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Phi 4 Multimodal Instruct | Qwen1.5-110B |
|---|---|---|
| Input price | $0.9/1M tokens | $1.5/1M tokens |
| Output price | $0.9/1M tokens | $2.5/1M tokens |
| Providers |
Capabilities
| Capability | Phi 4 Multimodal Instruct | Qwen1.5-110B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Phi 4 Multimodal Instruct, multimodal input: Phi 4 Multimodal Instruct, and structured outputs: Qwen1.5-110B. 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 4 Multimodal Instruct lists $0.9/1M input and $0.9/1M output tokens, while Qwen1.5-110B lists $1.5/1M input and $2.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi 4 Multimodal Instruct lower by about $0.9 per million blended tokens. Availability is 3 providers versus 2, so concentration risk also matters.
Choose Phi 4 Multimodal Instruct when vision-heavy evaluation, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen1.5-110B when provider fit 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 is cheaper, Phi 4 Multimodal Instruct or Qwen1.5-110B?
Phi 4 Multimodal Instruct is cheaper on tracked token pricing. Phi 4 Multimodal Instruct costs $0.9/1M input and $0.9/1M output tokens. Qwen1.5-110B costs $1.5/1M input and $2.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Phi 4 Multimodal Instruct or Qwen1.5-110B open source?
Phi 4 Multimodal Instruct is listed under Open Source. Qwen1.5-110B 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 Multimodal Instruct or Qwen1.5-110B?
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, Phi 4 Multimodal Instruct or Qwen1.5-110B?
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.
Which is better for structured outputs, Phi 4 Multimodal Instruct or Qwen1.5-110B?
Qwen1.5-110B has the clearer documented structured outputs signal in this comparison. If structured outputs 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 Multimodal Instruct and Qwen1.5-110B?
Phi 4 Multimodal Instruct is available on Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Qwen1.5-110B is available on Microsoft Foundry and Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.