Gemini 2.5 Pro vs Mixtral 8x7B
Gemini 2.5 Pro (2025) and Mixtral 8x7B (2023) are frontier reasoning models from Google DeepMind and MistralAI. Gemini 2.5 Pro ships a 1m-token context window, while Mixtral 8x7B ships a 32k-token context window. On Google-Proof Q&A, Gemini 2.5 Pro leads by 31.6 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Gemini 2.5 Pro fits 31x more tokens; pick it for long-context work and Mixtral 8x7B for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemini 2.5 Pro | Mixtral 8x7B |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding and Classification |
| Context window | 1m | 32k |
| Cheapest output | $10/1M tokens | $0.45/1M tokens |
| Provider routes | 4 tracked | 18 tracked |
| Shared benchmarks | Google-Proof Q&A leader | 2 rows |
Decision tradeoffs
- Gemini 2.5 Pro holds a shared-benchmark lead on Google-Proof Q&A, ahead by 31.6 points.
- Gemini 2.5 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 2.5 Pro uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Gemini 2.5 Pro for Coding, RAG, and Agents.
- Mixtral 8x7B has the lower cheapest tracked output price at $0.45/1M tokens.
- Mixtral 8x7B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mixtral 8x7B for Coding and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemini 2.5 Pro
$3,500
Cheapest tracked route/tier: Google AI Studio <=200K tokens
Mixtral 8x7B
$233
Cheapest tracked route/tier: Mistral AI Studio
Estimated monthly gap: $3,268. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Mixtral 8x7B is $9.55/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Gemini 2.5 Pro is $9.55/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Gemini 2.5 Pro adds Vision, Multimodal, and Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-17 | 2023-12-11 |
| Context window | 1m | 32k |
| Parameters | — | 8x7B |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Apache 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-01 | 2023-12 |
Pricing and availability
| Pricing attribute | Gemini 2.5 Pro | Mixtral 8x7B |
|---|---|---|
| Input price |
| $0.15/1M tokens |
| Output price |
| $0.45/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 2.5 Pro | Mixtral 8x7B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Mixtral 8x7B |
|---|---|---|
| Google-Proof Q&A | 86.4 | 54.8 |
| HumanEval | 93.1 | 80.5 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Gemini 2.5 Pro at 86.4 and Mixtral 8x7B at 54.8, with Gemini 2.5 Pro ahead by 31.6 points; HumanEval has Gemini 2.5 Pro at 93.1 and Mixtral 8x7B at 80.5, with Gemini 2.5 Pro ahead by 12.6 points. The largest visible gap is 31.6 points on Google-Proof Q&A, 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 vision: Gemini 2.5 Pro, multimodal input: Gemini 2.5 Pro, reasoning mode: Gemini 2.5 Pro, function calling: Gemini 2.5 Pro, tool use: Gemini 2.5 Pro, structured outputs: Gemini 2.5 Pro, and code execution: Gemini 2.5 Pro. 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, Gemini 2.5 Pro lists tiered pricing: <=200K tokens is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output, while Mixtral 8x7B lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B lower by about $3.63 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 4 providers versus 18, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support and larger context windows are central to the workload. Choose Mixtral 8x7B when provider fit, lower input-token cost, 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, Gemini 2.5 Pro or Mixtral 8x7B?
Gemini 2.5 Pro supports 1m tokens, while Mixtral 8x7B supports 32k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemini 2.5 Pro or Mixtral 8x7B?
Gemini 2.5 Pro lists tiered pricing: <=200K tokens is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output. Mixtral 8x7B lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Mixtral 8x7B open source?
Gemini 2.5 Pro is listed under Proprietary. Mixtral 8x7B 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 vision, Gemini 2.5 Pro or Mixtral 8x7B?
Gemini 2.5 Pro has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Gemini 2.5 Pro or Mixtral 8x7B?
Gemini 2.5 Pro 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.
Where can I run Gemini 2.5 Pro and Mixtral 8x7B?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, OpenRouter, and Vercel AI Gateway. Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API (Deprecated). Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-05. Data sourced from public model cards and provider documentation.