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Phi-4 14B vs Together AI Deepseek-LLM-67B-Chat

Phi-4 14B (2024) and Together AI Deepseek-LLM-67B-Chat (2024) are compact production models from Microsoft Research and DeepSeek. Phi-4 14B ships a not-yet-sourced context window, while Together AI Deepseek-LLM-67B-Chat ships a 4K-token context window. On pricing, Phi-4 14B costs $0.07/1M input tokens versus $0.6/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

Phi-4 14B is ~823% cheaper at $0.07/1M; pay for Together AI Deepseek-LLM-67B-Chat only for provider fit.

Decision scorecard

Local evidence first
SignalPhi-4 14BTogether AI Deepseek-LLM-67B-Chat
Decision fitClassification and JSON / Tool useClassification and JSON / Tool use
Context window4K
Cheapest output$0.14/1M tokens$0.6/1M tokens
Provider routes3 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Phi-4 14B when...
  • Phi-4 14B has the lower cheapest tracked output price at $0.14/1M tokens.
  • Phi-4 14B has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Phi-4 14B for Classification and JSON / Tool use.
Choose Together AI Deepseek-LLM-67B-Chat when...
  • Together AI Deepseek-LLM-67B-Chat has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Together AI Deepseek-LLM-67B-Chat for Classification and JSON / Tool use.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate Phi-4 14B

Phi-4 14B

$87.00

Cheapest tracked route: OpenRouter

Together AI Deepseek-LLM-67B-Chat

$630

Cheapest tracked route: Together AI

Estimated monthly gap: $543. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Phi-4 14B -> Together AI Deepseek-LLM-67B-Chat
  • No overlapping tracked provider route is sourced for Phi-4 14B and Together AI Deepseek-LLM-67B-Chat; plan for SDK, billing, or endpoint changes.
  • Together AI Deepseek-LLM-67B-Chat is $0.46/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Together AI Deepseek-LLM-67B-Chat -> Phi-4 14B
  • No overlapping tracked provider route is sourced for Together AI Deepseek-LLM-67B-Chat and Phi-4 14B; plan for SDK, billing, or endpoint changes.
  • Phi-4 14B is $0.46/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.

Specs

Specification
Released2024-12-132024-01-09
Context window4K
Parameters14B67B
Architecturedecoder onlydecoder only
LicenseOpen SourceOpen Source
Knowledge cutoff--

Pricing and availability

Pricing attributePhi-4 14BTogether AI Deepseek-LLM-67B-Chat
Input price$0.07/1M tokens$0.6/1M tokens
Output price$0.14/1M tokens$0.6/1M tokens
Providers

Capabilities

CapabilityPhi-4 14BTogether AI Deepseek-LLM-67B-Chat
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsYesYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, Phi-4 14B lists $0.07/1M input and $0.14/1M output tokens, while Together AI Deepseek-LLM-67B-Chat lists $0.6/1M input and $0.6/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-4 14B lower by about $0.51 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.

Choose Phi-4 14B when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Together AI Deepseek-LLM-67B-Chat 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which is cheaper, Phi-4 14B or Together AI Deepseek-LLM-67B-Chat?

Phi-4 14B is cheaper on tracked token pricing. Phi-4 14B costs $0.07/1M input and $0.14/1M output tokens. Together AI Deepseek-LLM-67B-Chat costs $0.6/1M input and $0.6/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Phi-4 14B or Together AI Deepseek-LLM-67B-Chat open source?

Phi-4 14B is listed under Open Source. Together AI Deepseek-LLM-67B-Chat is listed under Open Source. 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 structured outputs, Phi-4 14B or Together AI Deepseek-LLM-67B-Chat?

Both Phi-4 14B and Together AI Deepseek-LLM-67B-Chat expose structured outputs. 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 14B and Together AI Deepseek-LLM-67B-Chat?

Phi-4 14B is available on OpenRouter, Fireworks AI, and Microsoft Foundry. Together AI Deepseek-LLM-67B-Chat is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Phi-4 14B over Together AI Deepseek-LLM-67B-Chat?

Phi-4 14B is ~823% cheaper at $0.07/1M; pay for Together AI Deepseek-LLM-67B-Chat only for provider fit. If your workload also depends on provider fit, start with Phi-4 14B; if it depends on provider fit, run the same evaluation with Together AI Deepseek-LLM-67B-Chat.

Continue comparing

Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.