Mixtral 8x22B v0.1 vs ShieldGemma 9B
Mixtral 8x22B v0.1 (2024) and ShieldGemma 9B (2024) are compact production models from MistralAI and Google DeepMind. Mixtral 8x22B v0.1 ships a 64k-token context window, while ShieldGemma 9B ships a 8k-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.
Mixtral 8x22B v0.1 fits 8x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls.
Decision scorecard
Local evidence first| Signal | Mixtral 8x22B v0.1 | ShieldGemma 9B |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Coding and Classification | Classification |
| Context window | 64k | 8k |
| Cheapest output | $0.65/1M 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 broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mixtral 8x22B v0.1 for Coding and Classification.
- Local decision data tags ShieldGemma 9B for Classification.
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
ShieldGemma 9B
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 | 2024-04-17 | 2024-07-01 |
| Context window | 64k | 8k |
| Parameters | 8x22B | 9B |
| Architecture | mixture of experts | decoder only |
| License | Apache 2.0(OSI) | Gemma |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | 2024-01 | - |
Pricing and availability
| Pricing attribute | Mixtral 8x22B v0.1 | ShieldGemma 9B |
|---|---|---|
| Input price | $0.65/1M tokens | - |
| Output price | $0.65/1M tokens | - |
| Providers |
Capabilities
| Capability | Mixtral 8x22B v0.1 | ShieldGemma 9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| 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 rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover the core production surface. 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.
Pricing coverage is uneven: Mixtral 8x22B v0.1 has $0.65/1M input tokens and ShieldGemma 9B has no token price sourced yet. Provider availability is 8 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Mixtral 8x22B v0.1 when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose ShieldGemma 9B 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Mixtral 8x22B v0.1 or ShieldGemma 9B?
Mixtral 8x22B v0.1 supports 64k tokens, while ShieldGemma 9B supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Mixtral 8x22B v0.1 or ShieldGemma 9B open source?
Mixtral 8x22B v0.1 is listed under Apache 2.0. ShieldGemma 9B is listed under Gemma. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Where can I run Mixtral 8x22B v0.1 and ShieldGemma 9B?
Mixtral 8x22B v0.1 is available on NVIDIA NIM, OctoAI API (Deprecated), Fireworks AI, DeepInfra, and Baseten API. ShieldGemma 9B is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Mixtral 8x22B v0.1 over ShieldGemma 9B?
Mixtral 8x22B v0.1 fits 8x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls. 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 ShieldGemma 9B.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.