Qwen3-105B vs ShieldGemma 9B
Qwen3-105B (2025) and ShieldGemma 9B (2024) are compact production models from Alibaba and Google DeepMind. Qwen3-105B ships a 128k-token context window, while ShieldGemma 9B ships a 8k-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.
Qwen3-105B fits 16x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls.
Decision scorecard
Local evidence first| Signal | Qwen3-105B | ShieldGemma 9B |
|---|---|---|
| Best for | tool-calling agents | general production evaluation |
| Decision fit | RAG, Agents, and Long context | Classification |
| Context window | 128k | 8k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Qwen3-105B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3-105B uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Qwen3-105B for RAG, Agents, and Long context.
- ShieldGemma 9B has broader tracked provider coverage for fallback and procurement flexibility.
- 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.
Qwen3-105B
Unavailable
No complete token price in local provider data
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
- No overlapping tracked provider route is sourced for Qwen3-105B and ShieldGemma 9B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- No overlapping tracked provider route is sourced for ShieldGemma 9B and Qwen3-105B; plan for SDK, billing, or endpoint changes.
- Qwen3-105B adds Function calling and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-15 | 2024-07-01 |
| Context window | 128k | 8k |
| Parameters | 105B | 9B |
| Architecture | - | decoder only |
| License | Open Source | 1 |
| Knowledge cutoff | 2025-02 | - |
Pricing and availability
| Pricing attribute | Qwen3-105B | ShieldGemma 9B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Qwen3-105B | ShieldGemma 9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | 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 differs most on function calling: Qwen3-105B and tool use: Qwen3-105B. 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: Qwen3-105B has no token price sourced yet and ShieldGemma 9B has no token price sourced yet. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Qwen3-105B when long-context analysis and larger context windows are central to the workload. Choose ShieldGemma 9B when provider fit 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. 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, Qwen3-105B or ShieldGemma 9B?
Qwen3-105B supports 128k 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Is Qwen3-105B or ShieldGemma 9B open source?
Qwen3-105B is listed under Open Source. ShieldGemma 9B is listed under 1. 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 function calling, Qwen3-105B or ShieldGemma 9B?
Qwen3-105B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Qwen3-105B or ShieldGemma 9B?
Qwen3-105B has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Qwen3-105B and ShieldGemma 9B?
Qwen3-105B is available on the tracked providers still being sourced. ShieldGemma 9B is available on NVIDIA NIM. 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 Qwen3-105B over ShieldGemma 9B?
Qwen3-105B fits 16x 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 Qwen3-105B; 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.