Gemma 2 27B Instruct vs Mixtral 8x22B v0.1
Gemma 2 27B Instruct (2024) and Mixtral 8x22B v0.1 (2024) are compact production models from Google DeepMind and MistralAI. Gemma 2 27B Instruct ships a 8K-token context window, while Mixtral 8x22B v0.1 ships a 64K-token context window. On Massive Multitask Language Understanding, Mixtral 8x22B v0.1 leads by 2.2 pts. On pricing, Gemma 2 27B Instruct costs $0.25/1M input tokens versus $0.3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Mixtral 8x22B v0.1 fits 8x more tokens; pick it for long-context work and Gemma 2 27B Instruct for tighter calls.
Specs
| Released | 2024-06-27 | 2024-04-17 |
| Context window | 8K | 64K |
| Parameters | 27B | 8x22B |
| Architecture | decoder only | mixture of experts |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Gemma 2 27B Instruct | Mixtral 8x22B v0.1 | |
|---|---|---|
| Input price | $0.25/1M tokens | $0.3/1M tokens |
| Output price | $0.75/1M tokens | $0.9/1M tokens |
| Providers |
Capabilities
| Gemma 2 27B Instruct | Mixtral 8x22B v0.1 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemma 2 27B Instruct | Mixtral 8x22B v0.1 |
|---|---|---|
| Massive Multitask Language Understanding | 82.3 | 84.5 |
Deep dive
On shared benchmark coverage, Massive Multitask Language Understanding has Gemma 2 27B Instruct at 82.3 and Mixtral 8x22B v0.1 at 84.5, with Mixtral 8x22B v0.1 ahead by 2.2 points. The largest visible gap is 2.2 points on Massive Multitask Language Understanding, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on structured outputs: Gemma 2 27B 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, Gemma 2 27B Instruct lists $0.25/1M input and $0.75/1M output tokens, while Mixtral 8x22B v0.1 lists $0.3/1M input and $0.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 2 27B Instruct lower by about $0.08 per million blended tokens. Availability is 5 providers versus 8, so concentration risk also matters.
Choose Gemma 2 27B Instruct when provider fit and lower input-token cost are central to the workload. Choose Mixtral 8x22B v0.1 when long-context analysis, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemma 2 27B Instruct or Mixtral 8x22B v0.1?
Mixtral 8x22B v0.1 supports 64K tokens, while Gemma 2 27B Instruct supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemma 2 27B Instruct or Mixtral 8x22B v0.1?
Gemma 2 27B Instruct is cheaper on tracked token pricing. Gemma 2 27B Instruct costs $0.25/1M input and $0.75/1M output tokens. Mixtral 8x22B v0.1 costs $0.3/1M input and $0.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 2 27B Instruct or Mixtral 8x22B v0.1 open source?
Gemma 2 27B Instruct is listed under Open Source. Mixtral 8x22B v0.1 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, Gemma 2 27B Instruct or Mixtral 8x22B v0.1?
Gemma 2 27B 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 Gemma 2 27B Instruct and Mixtral 8x22B v0.1?
Gemma 2 27B Instruct is available on NVIDIA NIM, OpenRouter, Fireworks AI, Arcee AI, and Replicate API. Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API, Fireworks AI, DeepInfra, and Baseten API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 2 27B Instruct over Mixtral 8x22B v0.1?
Mixtral 8x22B v0.1 fits 8x more tokens; pick it for long-context work and Gemma 2 27B Instruct for tighter calls. If your workload also depends on provider fit, start with Gemma 2 27B Instruct; if it depends on long-context analysis, run the same evaluation with Mixtral 8x22B v0.1.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.