Llama 3.2 90B Instruct vs Together AI Qwen2-7B-Instruct
Llama 3.2 90B Instruct (2025) and Together AI Qwen2-7B-Instruct (2024) are compact production models from AI at Meta and Alibaba. Llama 3.2 90B Instruct ships a not-yet-sourced context window, while Together AI Qwen2-7B-Instruct ships a 33K-token context window. On pricing, Together AI Qwen2-7B-Instruct costs $0.15/1M input tokens versus $1.35/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Together AI Qwen2-7B-Instruct is ~800% cheaper at $0.15/1M; pay for Llama 3.2 90B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | Llama 3.2 90B Instruct | Together AI Qwen2-7B-Instruct |
|---|---|---|
| Decision fit | Classification and JSON / Tool use | Classification and JSON / Tool use |
| Context window | — | 33K |
| Cheapest output | $1.8/1M tokens | $0.15/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Llama 3.2 90B Instruct for Classification and JSON / Tool use.
- Together AI Qwen2-7B-Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Together AI Qwen2-7B-Instruct has the lower cheapest tracked output price at $0.15/1M tokens.
- Local decision data tags Together AI Qwen2-7B-Instruct for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3.2 90B Instruct
$1,530
Cheapest tracked route: AWS Bedrock
Together AI Qwen2-7B-Instruct
$158
Cheapest tracked route: Together AI
Estimated monthly gap: $1,373. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Llama 3.2 90B Instruct and Together AI Qwen2-7B-Instruct; plan for SDK, billing, or endpoint changes.
- Together AI Qwen2-7B-Instruct is $1.65/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- No overlapping tracked provider route is sourced for Together AI Qwen2-7B-Instruct and Llama 3.2 90B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.2 90B Instruct is $1.65/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-01 | 2024-06-07 |
| Context window | — | 33K |
| Parameters | — | 7B |
| Architecture | - | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Llama 3.2 90B Instruct | Together AI Qwen2-7B-Instruct |
|---|---|---|
| Input price | $1.35/1M tokens | $0.15/1M tokens |
| Output price | $1.8/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.2 90B Instruct | Together AI Qwen2-7B-Instruct |
|---|---|---|
| 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, Llama 3.2 90B Instruct lists $1.35/1M input and $1.8/1M output tokens, while Together AI Qwen2-7B-Instruct lists $0.15/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Together AI Qwen2-7B-Instruct lower by about $1.33 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Llama 3.2 90B Instruct when provider fit are central to the workload. Choose Together AI Qwen2-7B-Instruct when provider fit 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 is cheaper, Llama 3.2 90B Instruct or Together AI Qwen2-7B-Instruct?
Together AI Qwen2-7B-Instruct is cheaper on tracked token pricing. Llama 3.2 90B Instruct costs $1.35/1M input and $1.8/1M output tokens. Together AI Qwen2-7B-Instruct costs $0.15/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.2 90B Instruct or Together AI Qwen2-7B-Instruct open source?
Llama 3.2 90B Instruct is listed under Proprietary. Together AI Qwen2-7B-Instruct 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, Llama 3.2 90B Instruct or Together AI Qwen2-7B-Instruct?
Both Llama 3.2 90B Instruct and Together AI Qwen2-7B-Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Llama 3.2 90B Instruct and Together AI Qwen2-7B-Instruct?
Llama 3.2 90B Instruct is available on AWS Bedrock. Together AI Qwen2-7B-Instruct 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.
When should I pick Llama 3.2 90B Instruct over Together AI Qwen2-7B-Instruct?
Together AI Qwen2-7B-Instruct is ~800% cheaper at $0.15/1M; pay for Llama 3.2 90B Instruct only for provider fit. If your workload also depends on provider fit, start with Llama 3.2 90B Instruct; if it depends on provider fit, run the same evaluation with Together AI Qwen2-7B-Instruct.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.