LLM Reference

Qwen2.5-Coder-14B vs Together AI Qwen2-7B-Instruct

Qwen2.5-Coder-14B (2024) and Together AI Qwen2-7B-Instruct (2024) compare a coding-specialized model against a standalone API model. Qwen2.5-Coder-14B ships a 128k-token context window, while Together AI Qwen2-7B-Instruct ships a 33k-token context window. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: Qwen2.5-Coder-14B is coding-specialized model, while Together AI Qwen2-7B-Instruct is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalQwen2.5-Coder-14BTogether AI Qwen2-7B-Instruct
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents and code generationgeneral production evaluation
Decision fitCoding and Long contextClassification and JSON / Tool use
Context window128k33k
Cheapest output-$0.15/1M tokens
Provider routes0 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Qwen2.5-Coder-14B when...
  • Qwen2.5-Coder-14B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Qwen2.5-Coder-14B for Coding and Long context.
Choose Together AI Qwen2-7B-Instruct when...
  • Together AI Qwen2-7B-Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Together AI Qwen2-7B-Instruct uniquely exposes Structured outputs in local model data.
  • Local decision data tags Together AI Qwen2-7B-Instruct for Classification and JSON / Tool use.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Qwen2.5-Coder-14B

Unavailable

No complete token price in local provider data

Together AI Qwen2-7B-Instruct

$158

Cheapest tracked route/tier: Together AI

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Qwen2.5-Coder-14B -> Together AI Qwen2-7B-Instruct
  • No overlapping tracked provider route is sourced for Qwen2.5-Coder-14B and Together AI Qwen2-7B-Instruct; plan for SDK, billing, or endpoint changes.
  • Together AI Qwen2-7B-Instruct adds Structured outputs in local capability data.
Together AI Qwen2-7B-Instruct -> Qwen2.5-Coder-14B
  • No overlapping tracked provider route is sourced for Together AI Qwen2-7B-Instruct and Qwen2.5-Coder-14B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2024-11-122024-06-07
Context window128k33k
Parameters14B7B
Architecturedecoder onlydecoder only
LicenseApache 2.0Open Source
Knowledge cutoff2024-02-

Pricing and availability

Pricing attributeQwen2.5-Coder-14BTogether AI Qwen2-7B-Instruct
Input price-$0.15/1M tokens
Output price-$0.15/1M tokens
Providers-

Capabilities

CapabilityQwen2.5-Coder-14BTogether AI Qwen2-7B-Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Together AI Qwen2-7B-Instruct. 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.

Pricing coverage is uneven: Qwen2.5-Coder-14B has no token price sourced yet and Together AI Qwen2-7B-Instruct has $0.15/1M input tokens. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Qwen2.5-Coder-14B when coding workflow support and larger context windows are central to the workload. Choose Together AI Qwen2-7B-Instruct when provider fit and broader provider choice 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 has a larger context window, Qwen2.5-Coder-14B or Together AI Qwen2-7B-Instruct?

Qwen2.5-Coder-14B supports 128k tokens, while Together AI Qwen2-7B-Instruct supports 33k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Qwen2.5-Coder-14B or Together AI Qwen2-7B-Instruct open source?

Qwen2.5-Coder-14B is listed under Apache 2.0. Together AI Qwen2-7B-Instruct 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, Qwen2.5-Coder-14B or Together AI Qwen2-7B-Instruct?

Together AI Qwen2-7B-Instruct 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 Qwen2.5-Coder-14B and Together AI Qwen2-7B-Instruct?

Qwen2.5-Coder-14B is available on the tracked providers still being sourced. Together AI Qwen2-7B-Instruct is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Qwen2.5-Coder-14B over Together AI Qwen2-7B-Instruct?

Treat this as a product-type comparison: Qwen2.5-Coder-14B is coding-specialized model, while Together AI Qwen2-7B-Instruct is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive. If your workload also depends on coding workflow support, start with Qwen2.5-Coder-14B; if it depends on provider fit, run the same evaluation with Together AI Qwen2-7B-Instruct.

Continue comparing

Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.