Mixtral 8x22B v0.1 vs Together AI Qwen2-72B-Instruct
Mixtral 8x22B v0.1 (2024) and Together AI Qwen2-72B-Instruct (2024) are compact production models from MistralAI and Alibaba. Mixtral 8x22B v0.1 ships a 64k-token context window, while Together AI Qwen2-72B-Instruct ships a 33k-token context window. On pricing, Mixtral 8x22B v0.1 costs $0.65/1M input tokens versus $0.70/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Together AI Qwen2-72B-Instruct is safer overall; choose Mixtral 8x22B v0.1 when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Mixtral 8x22B v0.1 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Coding and Classification | Classification and JSON / Tool use |
| Context window | 64k | 33k |
| Cheapest output | $0.65/1M tokens | $0.70/1M tokens |
| Provider routes | 8 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Mixtral 8x22B v0.1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mixtral 8x22B v0.1 has the lower cheapest tracked output price at $0.65/1M tokens.
- Mixtral 8x22B v0.1 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mixtral 8x22B v0.1 for Coding and Classification.
- Together AI Qwen2-72B-Instruct uniquely exposes Structured outputs in local model data.
- Local decision data tags Together AI Qwen2-72B-Instruct for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mixtral 8x22B v0.1
$683
Cheapest tracked route/tier: DeepInfra
Together AI Qwen2-72B-Instruct
$735
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $52.50. Batch, cache, alternate speed tiers, 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 Qwen2-72B-Instruct is $0.05/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Together AI Qwen2-72B-Instruct adds Structured outputs in local capability data.
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Mixtral 8x22B v0.1 is $0.05/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-17 | 2024-06-07 |
| Context window | 64k | 33k |
| Parameters | 8x22B | 72B |
| Architecture | mixture of experts | decoder only |
| License | Apache 2.0(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2024-01 | - |
Pricing and availability
| Pricing attribute | Mixtral 8x22B v0.1 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Input price | $0.65/1M tokens | $0.70/1M tokens |
| Output price | $0.65/1M tokens | $0.70/1M tokens |
| Providers |
Capabilities
| Capability | Mixtral 8x22B v0.1 | Together AI Qwen2-72B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| 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: Together AI Qwen2-72B-Instruct. 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, Mixtral 8x22B v0.1 lists $0.65/1M input and $0.65/1M output tokens on the cheapest tracked provider, while Together AI Qwen2-72B-Instruct lists $0.70/1M input and $0.70/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x22B v0.1 lower by about $0.05 per million blended tokens. Availability is 8 providers versus 1, so concentration risk also matters.
Choose Mixtral 8x22B v0.1 when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Together AI Qwen2-72B-Instruct 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.
FAQ
Which has a larger context window, Mixtral 8x22B v0.1 or Together AI Qwen2-72B-Instruct?
Mixtral 8x22B v0.1 supports 64k tokens, while Together AI Qwen2-72B-Instruct supports 33k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Mixtral 8x22B v0.1 or Together AI Qwen2-72B-Instruct?
Mixtral 8x22B v0.1 is cheaper on tracked token pricing. Mixtral 8x22B v0.1 costs $0.65/1M input and $0.65/1M output tokens. Together AI Qwen2-72B-Instruct costs $0.70/1M input and $0.70/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Mixtral 8x22B v0.1 or Together AI Qwen2-72B-Instruct open source?
Mixtral 8x22B v0.1 is listed under Apache 2.0. Together AI Qwen2-72B-Instruct 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, Mixtral 8x22B v0.1 or Together AI Qwen2-72B-Instruct?
Together AI Qwen2-72B-Instruct 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 Mixtral 8x22B v0.1 and Together AI Qwen2-72B-Instruct?
Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API (Deprecated), Fireworks AI, DeepInfra, and Baseten API. Together AI Qwen2-72B-Instruct is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Mixtral 8x22B v0.1 over Together AI Qwen2-72B-Instruct?
Together AI Qwen2-72B-Instruct is safer overall; choose Mixtral 8x22B v0.1 when long-context analysis matters. If your workload also depends on long-context analysis, start with Mixtral 8x22B v0.1; if it depends on provider fit, run the same evaluation with Together AI Qwen2-72B-Instruct.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.