Qwen2-72B vs Qwen2.5-Coder-14B-Instruct
Qwen2-72B (2024) and Qwen2.5-Coder-14B-Instruct (2024) compare a standalone API model against a coding-specialized model. Qwen2-72B ships a 128k-token context window, while Qwen2.5-Coder-14B-Instruct ships a 128k-token context window. On pricing, Qwen2.5-Coder-14B-Instruct costs $0.20/1M input tokens versus $0.45/1M 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: Qwen2-72B is standalone API model, while Qwen2.5-Coder-14B-Instruct is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | Qwen2-72B | Qwen2.5-Coder-14B-Instruct |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | provider-routed production | custom coding agents and code generation |
| Decision fit | Coding, RAG, and Long context | Coding and Long context |
| Context window | 128k | 128k |
| Cheapest output | $0.65/1M tokens | $0.20/1M tokens |
| Provider routes | 4 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Qwen2-72B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen2-72B uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen2-72B for Coding, RAG, and Long context.
- Qwen2.5-Coder-14B-Instruct has the lower cheapest tracked output price at $0.20/1M tokens.
- Local decision data tags Qwen2.5-Coder-14B-Instruct for Coding and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Qwen2-72B
$523
Cheapest tracked route/tier: DeepInfra
Qwen2.5-Coder-14B-Instruct
$210
Cheapest tracked route/tier: Fireworks AI
Estimated monthly gap: $313. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Qwen2.5-Coder-14B-Instruct is $0.45/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Qwen2-72B is $0.45/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen2-72B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-06-05 | 2024-11-12 |
| Context window | 128k | 128k |
| Parameters | 72.71B | 14B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Apache 2.0 |
| Knowledge cutoff | - | 2024-02 |
Pricing and availability
| Pricing attribute | Qwen2-72B | Qwen2.5-Coder-14B-Instruct |
|---|---|---|
| Input price | $0.45/1M tokens | $0.20/1M tokens |
| Output price | $0.65/1M tokens | $0.20/1M tokens |
| Providers |
Capabilities
| Capability | Qwen2-72B | Qwen2.5-Coder-14B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Qwen2-72B. 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, Qwen2-72B lists $0.45/1M input and $0.65/1M output tokens on the cheapest tracked provider, while Qwen2.5-Coder-14B-Instruct lists $0.20/1M input and $0.20/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2.5-Coder-14B-Instruct lower by about $0.31 per million blended tokens. Availability is 4 providers versus 1, so concentration risk also matters.
Choose Qwen2-72B when provider fit and broader provider choice are central to the workload. Choose Qwen2.5-Coder-14B-Instruct when coding workflow support 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. 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, Qwen2-72B or Qwen2.5-Coder-14B-Instruct?
Qwen2-72B supports 128k tokens, while Qwen2.5-Coder-14B-Instruct supports 128k 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, Qwen2-72B or Qwen2.5-Coder-14B-Instruct?
Qwen2.5-Coder-14B-Instruct is cheaper on tracked token pricing. Qwen2-72B costs $0.45/1M input and $0.65/1M output tokens. Qwen2.5-Coder-14B-Instruct costs $0.20/1M input and $0.20/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Qwen2-72B or Qwen2.5-Coder-14B-Instruct open source?
Qwen2-72B is listed under Apache 2.0. Qwen2.5-Coder-14B-Instruct 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 structured outputs, Qwen2-72B or Qwen2.5-Coder-14B-Instruct?
Qwen2-72B 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 Qwen2-72B and Qwen2.5-Coder-14B-Instruct?
Qwen2-72B is available on Fireworks AI, DeepInfra, Together AI, and Microsoft Foundry. Qwen2.5-Coder-14B-Instruct is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Qwen2-72B over Qwen2.5-Coder-14B-Instruct?
Treat this as a product-type comparison: Qwen2-72B is standalone API model, while Qwen2.5-Coder-14B-Instruct is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive. If your workload also depends on provider fit, start with Qwen2-72B; if it depends on coding workflow support, run the same evaluation with Qwen2.5-Coder-14B-Instruct.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.