Qwen2-72B vs Qwen2.5-Coder-1.5B
Qwen2-72B (2024) and Qwen2.5-Coder-1.5B (2024) compare a standalone API model against a coding-specialized model. Qwen2-72B ships a 128k-token context window, while Qwen2.5-Coder-1.5B ships a 32k-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: Qwen2-72B is standalone API model, while Qwen2.5-Coder-1.5B 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-1.5B |
|---|---|---|
| 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 |
| Context window | 128k | 32k |
| Cheapest output | $0.65/1M tokens | - |
| Provider routes | 4 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Qwen2-72B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- 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.
- Local decision data tags Qwen2.5-Coder-1.5B for Coding.
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-1.5B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Qwen2-72B and Qwen2.5-Coder-1.5B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Qwen2.5-Coder-1.5B and Qwen2-72B; plan for SDK, billing, or endpoint changes.
- Qwen2-72B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-06-05 | 2024-09-19 |
| Context window | 128k | 32k |
| Parameters | 72.71B | 1.54B |
| 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-1.5B |
|---|---|---|
| Input price | $0.45/1M tokens | - |
| Output price | $0.65/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Qwen2-72B | Qwen2.5-Coder-1.5B |
|---|---|---|
| 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.
Pricing coverage is uneven: Qwen2-72B has $0.45/1M input tokens and Qwen2.5-Coder-1.5B has no token price sourced yet. Provider availability is 4 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Qwen2-72B when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Qwen2.5-Coder-1.5B when coding workflow support 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-1.5B?
Qwen2-72B supports 128k tokens, while Qwen2.5-Coder-1.5B supports 32k 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.
Is Qwen2-72B or Qwen2.5-Coder-1.5B open source?
Qwen2-72B is listed under Apache 2.0. Qwen2.5-Coder-1.5B 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-1.5B?
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-1.5B?
Qwen2-72B is available on Fireworks AI, DeepInfra, Together AI, and Microsoft Foundry. Qwen2.5-Coder-1.5B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Qwen2-72B over Qwen2.5-Coder-1.5B?
Treat this as a product-type comparison: Qwen2-72B is standalone API model, while Qwen2.5-Coder-1.5B is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive. If your workload also depends on long-context analysis, start with Qwen2-72B; if it depends on coding workflow support, run the same evaluation with Qwen2.5-Coder-1.5B.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.