Gemma 3 vs GLM-5
Gemma 3 (2025) and GLM-5 (2026) are frontier reasoning models from Google DeepMind and Zhipu AI. Gemma 3 ships a not-yet-sourced context window, while GLM-5 ships a 200k-token context window. On pricing, Gemma 3 costs $0.04/1M input tokens versus $0.60/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Gemma 3 is ~1400% cheaper at $0.04/1M; pay for GLM-5 only for reasoning depth.
Decision scorecard
Local evidence first| Signal | Gemma 3 | GLM-5 |
|---|---|---|
| Best for | provider-routed production | reasoning-heavy apps, tool-calling agents, and provider-routed production |
| Decision fit | Classification and JSON / Tool use | Coding, RAG, and Agents |
| Context window | — | 200k |
| Cheapest output | $0.08/1M tokens | $2.08/1M tokens |
| Provider routes | 3 tracked | 7 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3 has the lower cheapest tracked output price at $0.08/1M tokens.
- Local decision data tags Gemma 3 for Classification and JSON / Tool use.
- GLM-5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 3
$52.00
Cheapest tracked route/tier: OpenRouter
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $948. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and GCP Vertex AI; start route-level A/B tests there.
- GLM-5 is $2/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GLM-5 adds Reasoning, Function calling, and Tool use in local capability data.
- Provider overlap exists on OpenRouter and GCP Vertex AI; start route-level A/B tests there.
- Gemma 3 is $2/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-12 | 2026-02-11 |
| Context window | — | 200k |
| Parameters | — | 744B total, 40B active |
| Architecture | decoder only | mixture of experts |
| License | Gemma | MIT |
| Knowledge cutoff | 2025-01 | 2025-11 |
Pricing and availability
| Pricing attribute | Gemma 3 | GLM-5 |
|---|---|---|
| Input price | $0.04/1M tokens | $0.60/1M tokens |
| Output price | $0.08/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3 | GLM-5 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | 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 reasoning mode: GLM-5, function calling: GLM-5, and tool use: GLM-5. Both models share structured outputs, 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.
For cost, Gemma 3 lists $0.04/1M input and $0.08/1M output tokens on the cheapest tracked provider, while GLM-5 lists $0.60/1M input and $2.08/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 3 lower by about $0.99 per million blended tokens. Availability is 3 providers versus 7, so concentration risk also matters.
Choose Gemma 3 when provider fit and lower input-token cost are central to the workload. Choose GLM-5 when reasoning depth 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.
FAQ
Which is cheaper, Gemma 3 or GLM-5?
Gemma 3 is cheaper on tracked token pricing. Gemma 3 costs $0.04/1M input and $0.08/1M output tokens. GLM-5 costs $0.60/1M input and $2.08/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 3 or GLM-5 open source?
Gemma 3 is listed under Gemma. GLM-5 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 or GLM-5?
GLM-5 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 or GLM-5?
GLM-5 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 or GLM-5?
GLM-5 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 and GLM-5?
Gemma 3 is available on OpenRouter, Google AI Studio, and GCP Vertex AI. GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. 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.