ShieldGemma 9B vs Together AI Deepseek-LLM-67B-Chat
ShieldGemma 9B (2024) and Together AI Deepseek-LLM-67B-Chat (2024) are compact production models from Google DeepMind and DeepSeek. ShieldGemma 9B ships a 8K-token context window, while Together AI Deepseek-LLM-67B-Chat ships a 4K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
ShieldGemma 9B is safer overall; choose Together AI Deepseek-LLM-67B-Chat when provider fit matters.
Decision scorecard
Local evidence first| Signal | ShieldGemma 9B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Decision fit | Classification | Classification and JSON / Tool use |
| Context window | 8K | 4K |
| Cheapest output | - | $0.6/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- ShieldGemma 9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags ShieldGemma 9B for Classification.
- Together AI Deepseek-LLM-67B-Chat uniquely exposes Structured outputs in local model data.
- Local decision data tags Together AI Deepseek-LLM-67B-Chat for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
ShieldGemma 9B
Unavailable
No complete token price in local provider data
Together AI Deepseek-LLM-67B-Chat
$630
Cheapest tracked route: Together AI
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for ShieldGemma 9B and Together AI Deepseek-LLM-67B-Chat; plan for SDK, billing, or endpoint changes.
- Together AI Deepseek-LLM-67B-Chat adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Together AI Deepseek-LLM-67B-Chat and ShieldGemma 9B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-01 | 2024-01-09 |
| Context window | 8K | 4K |
| Parameters | 9B | 67B |
| Architecture | decoder only | decoder only |
| License | 1 | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | ShieldGemma 9B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| Input price | - | $0.6/1M tokens |
| Output price | - | $0.6/1M tokens |
| Providers |
Capabilities
| Capability | ShieldGemma 9B | Together AI Deepseek-LLM-67B-Chat |
|---|---|---|
| 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 |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Together AI Deepseek-LLM-67B-Chat. 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.
Pricing coverage is uneven: ShieldGemma 9B has no token price sourced yet and Together AI Deepseek-LLM-67B-Chat has $0.6/1M input tokens. Provider availability is 1 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose ShieldGemma 9B when long-context analysis and larger context windows are central to the workload. Choose Together AI Deepseek-LLM-67B-Chat 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, ShieldGemma 9B or Together AI Deepseek-LLM-67B-Chat?
ShieldGemma 9B supports 8K tokens, while Together AI Deepseek-LLM-67B-Chat supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is ShieldGemma 9B or Together AI Deepseek-LLM-67B-Chat open source?
ShieldGemma 9B is listed under 1. Together AI Deepseek-LLM-67B-Chat is listed under Open Source. 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, ShieldGemma 9B or Together AI Deepseek-LLM-67B-Chat?
Together AI Deepseek-LLM-67B-Chat 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 ShieldGemma 9B and Together AI Deepseek-LLM-67B-Chat?
ShieldGemma 9B is available on NVIDIA NIM. Together AI Deepseek-LLM-67B-Chat is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
When should I pick ShieldGemma 9B over Together AI Deepseek-LLM-67B-Chat?
ShieldGemma 9B is safer overall; choose Together AI Deepseek-LLM-67B-Chat when provider fit matters. If your workload also depends on long-context analysis, start with ShieldGemma 9B; if it depends on provider fit, run the same evaluation with Together AI Deepseek-LLM-67B-Chat.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.