Qwen3.5-Flash vs Together AI Deepseek-LLM-67B-Chat
Qwen3.5-Flash (2026) and Together AI Deepseek-LLM-67B-Chat (2024) are compact production models from Alibaba and DeepSeek. Qwen3.5-Flash ships a 1M-token context window, while Together AI Deepseek-LLM-67B-Chat ships a 4K-token context window. On pricing, Qwen3.5-Flash costs $0.07/1M 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-Flash is ~757% cheaper at $0.07/1M; pay for Together AI Deepseek-LLM-67B-Chat only for provider fit.
Decision scorecard
Local evidence first| Signal | Qwen3.5-Flash | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Decision fit | Long context and Vision | Classification and JSON / Tool use |
| Context window | 1M | 4K |
| Cheapest output | $0.26/1M tokens | $0.6/1M tokens |
| Provider routes | 2 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Qwen3.5-Flash has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-Flash has the lower cheapest tracked output price at $0.26/1M tokens.
- Qwen3.5-Flash has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-Flash uniquely exposes Multimodal in local model data.
- Local decision data tags Qwen3.5-Flash for Long context and Vision.
- Together AI Deepseek-LLM-67B-Chat uniquely exposes Structured outputs in local model data.
- 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-Flash
$121
Cheapest tracked route: OpenRouter
Together AI Deepseek-LLM-67B-Chat
$630
Cheapest tracked route: Together AI
Estimated monthly gap: $509. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Qwen3.5-Flash and Together AI Deepseek-LLM-67B-Chat; plan for SDK, billing, or endpoint changes.
- Together AI Deepseek-LLM-67B-Chat is $0.34/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Multimodal before moving production traffic.
- Together AI Deepseek-LLM-67B-Chat adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Together AI Deepseek-LLM-67B-Chat and Qwen3.5-Flash; plan for SDK, billing, or endpoint changes.
- Qwen3.5-Flash is $0.34/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
- Qwen3.5-Flash adds Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-23 | 2024-01-09 |
| Context window | 1M | 4K |
| Parameters | — | 67B |
| Architecture | - | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Qwen3.5-Flash | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Input price | $0.07/1M tokens | $0.6/1M tokens |
| Output price | $0.26/1M tokens | $0.6/1M tokens |
| Providers |
Capabilities
| Capability | Qwen3.5-Flash | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Vision | No | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: Qwen3.5-Flash and structured outputs: Together AI Deepseek-LLM-67B-Chat. 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, Qwen3.5-Flash lists $0.07/1M input and $0.26/1M 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-Flash lower by about $0.47 per million blended tokens. Availability is 2 providers versus 1, so concentration risk also matters.
Choose Qwen3.5-Flash 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-Flash or Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-Flash supports 1M 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-Flash or Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-Flash is cheaper on tracked token pricing. Qwen3.5-Flash costs $0.07/1M input and $0.26/1M 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-Flash or Together AI Deepseek-LLM-67B-Chat open source?
Qwen3.5-Flash is listed under Proprietary. 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 multimodal input, Qwen3.5-Flash or Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-Flash 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.
Which is better for structured outputs, Qwen3.5-Flash or Together AI Deepseek-LLM-67B-Chat?
Together AI Deepseek-LLM-67B-Chat 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 Qwen3.5-Flash and Together AI Deepseek-LLM-67B-Chat?
Qwen3.5-Flash is available on Alibaba Cloud PAI-EAS and OpenRouter. Together AI Deepseek-LLM-67B-Chat is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.