Mixtral 8x7B vs Qwen2-7B-Instruct
Mixtral 8x7B (2023) and Qwen2-7B-Instruct (2024) are compact production models from MistralAI and Alibaba. Mixtral 8x7B ships a 32k-token context window, while Qwen2-7B-Instruct ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Qwen2-7B-Instruct fits 4x more tokens; pick it for long-context work and Mixtral 8x7B for tighter calls.
Decision scorecard
Local evidence first| Signal | Mixtral 8x7B | Qwen2-7B-Instruct |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Coding and Classification | Long context |
| Context window | 32k | 128k |
| Cheapest output | $0.45/1M tokens | - |
| Provider routes | 18 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Mixtral 8x7B has broader tracked provider coverage for fallback and route flexibility.
- Local decision data tags Mixtral 8x7B for Coding and Classification.
- Qwen2-7B-Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Qwen2-7B-Instruct for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Mixtral 8x7B
$233
Cheapest tracked route/tier: Mistral AI Studio
Qwen2-7B-Instruct
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-12-11 | 2024-06-07 |
| Context window | 32k | 128k |
| Parameters | 8x7B | 7B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Apache 2.0OSI-approved | Apache 2.0OSI-approved |
| Openness | Open source | Open source |
| Weights | Unknown | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Mixtral 8x7B | Qwen2-7B-Instruct |
|---|---|---|
| Input price | $0.15/1M tokens | - |
| Output price | $0.45/1M tokens | - |
| Providers |
Capabilities
| Capability | Mixtral 8x7B | Qwen2-7B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| JSON / Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Continue comparing
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- MiniCPM-V 4.6 vs Qwen2-7B-Instruct
Popular comparisons for Mixtral 8x7B
Popular comparisons for Qwen2-7B-Instruct
Last reviewed: 2026-07-11. Data sourced from public model cards and provider documentation.