Gemma 3 12B vs GLM-5 9B
Gemma 3 12B (2026) and GLM-5 9B (2026) are frontier reasoning models from Google DeepMind and Zhipu AI. Gemma 3 12B ships a 33k-token context window, while GLM-5 9B ships a 262k-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.
GLM-5 9B fits 8x more tokens; pick it for long-context work and Gemma 3 12B for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemma 3 12B | GLM-5 9B |
|---|---|---|
| Best for | provider-routed production | reasoning-heavy apps and tool-calling agents |
| Decision fit | Classification and JSON / Tool use | RAG, Agents, and Long context |
| Context window | 33k | 262k |
| Cheapest output | $0.13/1M tokens | - |
| Provider routes | 5 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3 12B has broader tracked provider coverage for fallback and procurement flexibility.
- Gemma 3 12B uniquely exposes Structured outputs in local model data.
- Local decision data tags Gemma 3 12B for Classification and JSON / Tool use.
- GLM-5 9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 9B uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GLM-5 9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 3 12B
$64.50
Cheapest tracked route/tier: OpenRouter
GLM-5 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 Gemma 3 12B and GLM-5 9B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- GLM-5 9B adds Reasoning, Function calling, and Tool use in local capability data.
- No overlapping tracked provider route is sourced for GLM-5 9B and Gemma 3 12B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- Gemma 3 12B adds Structured outputs in local capability data.
Specs
Pricing and availability
| Pricing attribute | Gemma 3 12B | GLM-5 9B |
|---|---|---|
| Input price | $0.04/1M tokens | - |
| Output price | $0.13/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Gemma 3 12B | GLM-5 9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | 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 reasoning mode: GLM-5 9B, function calling: GLM-5 9B, tool use: GLM-5 9B, and structured outputs: Gemma 3 12B. 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: Gemma 3 12B has $0.04/1M input tokens and GLM-5 9B has no token price sourced yet. Provider availability is 5 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 3 12B when provider fit and broader provider choice are central to the workload. Choose GLM-5 9B when reasoning depth and larger context windows 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.
FAQ
Which has a larger context window, Gemma 3 12B or GLM-5 9B?
GLM-5 9B supports 262k tokens, while Gemma 3 12B supports 33k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 3 12B or GLM-5 9B open source?
Gemma 3 12B is listed under Gemma. GLM-5 9B is listed under MIT. 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 reasoning mode, Gemma 3 12B or GLM-5 9B?
GLM-5 9B has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, Gemma 3 12B or GLM-5 9B?
GLM-5 9B 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, Gemma 3 12B or GLM-5 9B?
GLM-5 9B 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 Gemma 3 12B and GLM-5 9B?
Gemma 3 12B is available on Cloudflare Workers AI, AWS Bedrock, OpenRouter, GCP Vertex AI, and Novita AI. GLM-5 9B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.