Qwen3.5-9B vs Together AI Deepseek-LLM-67B-Chat
Qwen3.5-9B (2026) and Together AI Deepseek-LLM-67B-Chat (2024) are compact production models from Alibaba and DeepSeek. Qwen3.5-9B ships a 262K-token context window, while Together AI Deepseek-LLM-67B-Chat ships a 4K-token context window. On pricing, Qwen3.5-9B costs $0.1/1M 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.
Qwen3.5-9B is ~500% cheaper at $0.1/1M; pay for Together AI Deepseek-LLM-67B-Chat only for provider fit.
Decision scorecard
Local evidence first| Signal | Qwen3.5-9B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | Classification and JSON / Tool use |
| Context window | 262K | 4K |
| Cheapest output | $0.15/1M tokens | $0.6/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-9B uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Qwen3.5-9B for RAG, Agents, and Long context.
- 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.
Qwen3.5-9B
$118
Cheapest tracked route: Together AI
Together AI Deepseek-LLM-67B-Chat
$630
Cheapest tracked route: Together AI
Estimated monthly gap: $513. 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 $0.45/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Qwen3.5-9B is $0.45/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Qwen3.5-9B adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-02 | 2024-01-09 |
| Context window | 262K | 4K |
| Parameters | 9B | 67B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0 | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Qwen3.5-9B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Input price | $0.1/1M tokens | $0.6/1M tokens |
| Output price | $0.15/1M tokens | $0.6/1M tokens |
| Providers |
Capabilities
| Capability | Qwen3.5-9B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | 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 differs most on vision: Qwen3.5-9B, multimodal input: Qwen3.5-9B, function calling: Qwen3.5-9B, and tool use: Qwen3.5-9B. Both models share structured outputs, 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, Qwen3.5-9B lists $0.1/1M input and $0.15/1M 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 Qwen3.5-9B lower by about $0.48 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Qwen3.5-9B 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, Qwen3.5-9B or Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-9B supports 262K 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, Qwen3.5-9B or Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-9B is cheaper on tracked token pricing. Qwen3.5-9B costs $0.1/1M input and $0.15/1M 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 Qwen3.5-9B or Together AI Deepseek-LLM-67B-Chat open source?
Qwen3.5-9B 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 vision, Qwen3.5-9B or Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-9B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Qwen3.5-9B or Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-9B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Qwen3.5-9B and Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. Together AI Deepseek-LLM-67B-Chat is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.