Qwen2-72B vs Together AI Deepseek-LLM-67B-Chat
Qwen2-72B (2024) and Together AI Deepseek-LLM-67B-Chat (2024) are compact production models from Alibaba and DeepSeek. Qwen2-72B ships a 128K-token context window, while Together AI Deepseek-LLM-67B-Chat ships a 4K-token context window. On pricing, Qwen2-72B costs $0.45/1M 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.
Qwen2-72B fits 31x more tokens; pick it for long-context work and Together AI Deepseek-LLM-67B-Chat for tighter calls.
Decision scorecard
Local evidence first| Signal | Qwen2-72B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Decision fit | Coding, RAG, and Long context | Classification and JSON / Tool use |
| Context window | 128K | 4K |
| Cheapest output | $0.65/1M tokens | $0.6/1M tokens |
| Provider routes | 4 tracked | 1 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.
- Local decision data tags Qwen2-72B for Coding, RAG, and Long context.
- Together AI Deepseek-LLM-67B-Chat has the lower cheapest tracked output price at $0.6/1M tokens.
- 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.
Qwen2-72B
$523
Cheapest tracked route: DeepInfra
Together AI Deepseek-LLM-67B-Chat
$630
Cheapest tracked route: Together AI
Estimated monthly gap: $108. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Together AI Deepseek-LLM-67B-Chat is $0.05/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Qwen2-72B is $0.05/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-06-05 | 2024-01-09 |
| Context window | 128K | 4K |
| Parameters | 72.71B | 67B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Qwen2-72B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Input price | $0.45/1M tokens | $0.6/1M tokens |
| Output price | $0.65/1M tokens | $0.6/1M tokens |
| Providers |
Capabilities
| Capability | Qwen2-72B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
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, Qwen2-72B lists $0.45/1M input and $0.65/1M 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 Qwen2-72B lower by about $0.09 per million blended tokens. Availability is 4 providers versus 1, so concentration risk also matters.
Choose Qwen2-72B when long-context analysis, larger context windows, and lower input-token cost 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 has a larger context window, Qwen2-72B or Together AI Deepseek-LLM-67B-Chat?
Qwen2-72B supports 128K tokens, while Together AI Deepseek-LLM-67B-Chat supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Qwen2-72B or Together AI Deepseek-LLM-67B-Chat?
Qwen2-72B is cheaper on tracked token pricing. Qwen2-72B costs $0.45/1M input and $0.65/1M 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 Qwen2-72B or Together AI Deepseek-LLM-67B-Chat open source?
Qwen2-72B is listed under Apache 2.0. 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, Qwen2-72B or Together AI Deepseek-LLM-67B-Chat?
Both Qwen2-72B 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Qwen2-72B and Together AI Deepseek-LLM-67B-Chat?
Qwen2-72B is available on Fireworks AI, DeepInfra, Together 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 Qwen2-72B over Together AI Deepseek-LLM-67B-Chat?
Qwen2-72B fits 31x more tokens; pick it for long-context work and Together AI Deepseek-LLM-67B-Chat for tighter calls. If your workload also depends on long-context analysis, start with Qwen2-72B; 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.