LLM Reference

Phi 4 Multimodal Instruct vs Qwen3.6-35B-A3B

Phi 4 Multimodal Instruct (2025) and Qwen3.6-35B-A3B (2026) compare a standalone API model against a coding-specialized model. Phi 4 Multimodal Instruct ships a 128k-token context window, while Qwen3.6-35B-A3B ships a 262k-token context window. On MMMU Pro, Qwen3.6-35B-A3B leads by 36.8 pts. On pricing, Qwen3.6-35B-A3B costs $0.15/1M input tokens versus $0.90/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: Phi 4 Multimodal Instruct is standalone API model, while Qwen3.6-35B-A3B is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalPhi 4 Multimodal InstructQwen3.6-35B-A3B
Product typeStandalone API modelCoding-specialized model
Best formultimodal apps and provider-routed productioncustom coding agents, code generation, and tool loops
Decision fitLong context and VisionCoding, RAG, and Agents
Context window128k262k
Cheapest output$0.90/1M tokens$1/1M tokens
Provider routes3 tracked2 tracked
Shared benchmarks1 rowsMMMU Pro leader

Decision tradeoffs

Choose Phi 4 Multimodal Instruct when...
  • Phi 4 Multimodal Instruct has the lower cheapest tracked output price at $0.90/1M tokens.
  • Phi 4 Multimodal Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Phi 4 Multimodal Instruct for Long context and Vision.
Choose Qwen3.6-35B-A3B when...
  • Qwen3.6-35B-A3B holds a shared-benchmark lead on MMMU Pro, ahead by 36.8 points.
  • Qwen3.6-35B-A3B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.6-35B-A3B uniquely exposes Function calling and Tool use in local model data.
  • Local decision data tags Qwen3.6-35B-A3B 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.

Lower estimate Qwen3.6-35B-A3B

Phi 4 Multimodal Instruct

$945

Cheapest tracked route/tier: Fireworks AI

Qwen3.6-35B-A3B

$370

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $575. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Phi 4 Multimodal Instruct -> Qwen3.6-35B-A3B
  • No overlapping tracked provider route is sourced for Phi 4 Multimodal Instruct and Qwen3.6-35B-A3B; plan for SDK, billing, or endpoint changes.
  • Qwen3.6-35B-A3B is $0.10/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Qwen3.6-35B-A3B adds Function calling and Tool use in local capability data.
Qwen3.6-35B-A3B -> Phi 4 Multimodal Instruct
  • No overlapping tracked provider route is sourced for Qwen3.6-35B-A3B and Phi 4 Multimodal Instruct; plan for SDK, billing, or endpoint changes.
  • Phi 4 Multimodal Instruct is $0.10/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Function calling and Tool use before moving production traffic.

Specs

Specification
Released2025-01-012026-04-16
Context window128k262k
Parameters5.6B35B
Architecturedecoder onlymoe
LicenseMIT(OSI)Apache 2.0(OSI)
OpennessOpen sourceOpen source
Commercial useCommercial use allowedCommercial use allowed
Knowledge cutoff2024-06-

Pricing and availability

Pricing attributePhi 4 Multimodal InstructQwen3.6-35B-A3B
Input price$0.90/1M tokens$0.15/1M tokens
Output price$0.90/1M tokens$1/1M tokens
Providers

Capabilities

CapabilityPhi 4 Multimodal InstructQwen3.6-35B-A3B
VisionYesYes
MultimodalYesYes
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsNoNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkPhi 4 Multimodal InstructQwen3.6-35B-A3B
MMMU Pro38.575.3

Deep dive

On shared benchmark coverage, MMMU Pro has Phi 4 Multimodal Instruct at 38.5 and Qwen3.6-35B-A3B at 75.3, with Qwen3.6-35B-A3B ahead by 36.8 points. The largest visible gap is 36.8 points on MMMU 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 function calling: Qwen3.6-35B-A3B and tool use: Qwen3.6-35B-A3B. Both models share vision and multimodal input, 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 $0.90/1M input and $0.90/1M output tokens on the cheapest tracked provider, while Qwen3.6-35B-A3B lists $0.15/1M input and $1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.6-35B-A3B lower by about $0.50 per million blended tokens. Availability is 3 providers versus 2, so concentration risk also matters.

Choose Phi 4 Multimodal Instruct when vision-heavy evaluation and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B when coding workflow support, larger context windows, and lower input-token cost 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 Multimodal Instruct or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B supports 262k tokens, while Phi 4 Multimodal Instruct 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 4 Multimodal Instruct or Qwen3.6-35B-A3B?

Qwen3.6-35B-A3B is cheaper on tracked token pricing. Phi 4 Multimodal Instruct costs $0.90/1M input and $0.90/1M output tokens. Qwen3.6-35B-A3B costs $0.15/1M input and $1/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Phi 4 Multimodal Instruct or Qwen3.6-35B-A3B open source?

Phi 4 Multimodal Instruct is listed under MIT. Qwen3.6-35B-A3B 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 Qwen3.6-35B-A3B?

Both Phi 4 Multimodal Instruct and Qwen3.6-35B-A3B expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. 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 Multimodal Instruct or Qwen3.6-35B-A3B?

Both Phi 4 Multimodal Instruct and Qwen3.6-35B-A3B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run Phi 4 Multimodal Instruct and Qwen3.6-35B-A3B?

Phi 4 Multimodal Instruct is available on Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Qwen3.6-35B-A3B is available on OpenRouter and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.