Gemma 4 12B vs GLM-5V-Turbo
Gemma 4 12B (2026) and GLM-5V-Turbo (2026) are frontier-tier reasoning models from Google DeepMind and Zhipu AI. Gemma 4 12B ships a 256k-token context window, while GLM-5V-Turbo ships a 200k-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.
Gemma 4 12B is safer overall; choose GLM-5V-Turbo when vision-heavy evaluation matters.
Decision scorecard
Local evidence first| Signal | Gemma 4 12B | GLM-5V-Turbo |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | RAG, Agents, and Long context | RAG, Agents, and Long context |
| Context window | 256k | 200k |
| Cheapest output | - | $4/1M tokens |
| Provider routes | 2 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 4 12B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Gemma 4 12B for RAG, Agents, and Long context.
- GLM-5V-Turbo uniquely exposes Structured outputs in local model data.
- Local decision data tags GLM-5V-Turbo 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 4 12B
Unavailable
No complete token price in local provider data
GLM-5V-Turbo
$1,960
Cheapest tracked route/tier: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 4 12B and GLM-5V-Turbo; plan for SDK, billing, or endpoint changes.
- GLM-5V-Turbo adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for GLM-5V-Turbo and Gemma 4 12B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-06-03 | 2026-04-01 |
| Context window | 256k | 200k |
| Parameters | 11.9B | 744B total, 40B active |
| Architecture | encoder free unified multimodal | mixture of experts |
| License | Apache 2.0 | Proprietary |
| Knowledge cutoff | 2025-01 | 2025-11 |
Pricing and availability
| Pricing attribute | Gemma 4 12B | GLM-5V-Turbo |
|---|---|---|
| Input price | - | $1.20/1M tokens |
| Output price | - | $4/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 4 12B | GLM-5V-Turbo |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | Yes |
| 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 structured outputs: GLM-5V-Turbo. Both models share vision, multimodal input, reasoning mode, and function calling, 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 4 12B has no token price sourced yet and GLM-5V-Turbo has $1.20/1M input tokens. Provider availability is 2 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 4 12B when long-context analysis and larger context windows are central to the workload. Choose GLM-5V-Turbo when vision-heavy evaluation 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, Gemma 4 12B or GLM-5V-Turbo?
Gemma 4 12B supports 256k tokens, while GLM-5V-Turbo supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 4 12B or GLM-5V-Turbo open source?
Gemma 4 12B is listed under Apache 2.0. GLM-5V-Turbo is listed under Proprietary. 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, Gemma 4 12B or GLM-5V-Turbo?
Both Gemma 4 12B and GLM-5V-Turbo expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Gemma 4 12B or GLM-5V-Turbo?
Both Gemma 4 12B and GLM-5V-Turbo expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, Gemma 4 12B or GLM-5V-Turbo?
Both Gemma 4 12B and GLM-5V-Turbo expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Gemma 4 12B and GLM-5V-Turbo?
Gemma 4 12B is available on Hugging Face Inference Endpoints and Kaggle Models. GLM-5V-Turbo is available on OpenRouter and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-03. Data sourced from public model cards and provider documentation.