Gemini 3 Pro vs GLM-5
Gemini 3 Pro (2025) and GLM-5 (2026) are frontier reasoning models from Google DeepMind and Zhipu AI. Gemini 3 Pro ships a 1m-token context window, while GLM-5 ships a 200k-token context window. On SWE-bench Verified, GLM-5 leads by 1.6 pts. On pricing, GLM-5 costs $0.60/1M input tokens versus $1.25/1M 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.
GLM-5 is ~108% cheaper at $0.60/1M; pay for Gemini 3 Pro only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Gemini 3 Pro | GLM-5 |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and long-context analysis | reasoning-heavy apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 200k |
| Cheapest output | $5/1M tokens | $2.08/1M tokens |
| Provider routes | 2 tracked | 7 tracked |
| Shared benchmarks | 2 rows | SWE-bench Verified leader |
Decision tradeoffs
- Gemini 3 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3 Pro uniquely exposes Vision, Multimodal, and Code execution in local model data.
- Local decision data tags Gemini 3 Pro for Coding, RAG, and Agents.
- GLM-5 leads the largest shared benchmark signal on SWE-bench Verified by 1.6 points.
- GLM-5 has the lower cheapest tracked output price at $2.08/1M tokens.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5 uniquely exposes Reasoning and Structured outputs 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.
Gemini 3 Pro
$2,250
Cheapest tracked route/tier: GCP Vertex AI
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $1,250. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- GLM-5 is $2.92/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Code execution before moving production traffic.
- GLM-5 adds Reasoning and Structured outputs in local capability data.
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Gemini 3 Pro is $2.92/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Reasoning and Structured outputs before moving production traffic.
- Gemini 3 Pro adds Vision, Multimodal, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-11 | 2026-02-11 |
| Context window | 1m | 200k |
| Parameters | — | 744B total, 40B active |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | MIT |
| Knowledge cutoff | 2025-01 | 2025-11 |
Pricing and availability
| Pricing attribute | Gemini 3 Pro | GLM-5 |
|---|---|---|
| Input price | $1.25/1M tokens | $0.60/1M tokens |
| Output price | $5/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 3 Pro | GLM-5 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemini 3 Pro | GLM-5 |
|---|---|---|
| SWE-bench Verified | 76.2 | 77.8 |
| SWE-bench Pro | 42.5 | 55.1 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has Gemini 3 Pro at 76.2 and GLM-5 at 77.8, with GLM-5 ahead by 1.6 points; SWE-bench Pro has Gemini 3 Pro at 42.5 and GLM-5 at 55.1, with GLM-5 ahead by 12.6 points. The largest visible gap is 12.6 points on SWE-bench Pro, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Gemini 3 Pro, multimodal input: Gemini 3 Pro, reasoning mode: GLM-5, structured outputs: GLM-5, and code execution: Gemini 3 Pro. Both models share function calling and tool use, 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, Gemini 3 Pro lists $1.25/1M input and $5/1M 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 GLM-5 lower by about $1.33 per million blended tokens. Availability is 2 providers versus 7, so concentration risk also matters.
Choose Gemini 3 Pro when coding workflow support and larger context windows are central to the workload. Choose GLM-5 when reasoning depth, lower input-token cost, 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.
FAQ
Which has a larger context window, Gemini 3 Pro or GLM-5?
Gemini 3 Pro supports 1m tokens, while GLM-5 supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemini 3 Pro or GLM-5?
GLM-5 is cheaper on tracked token pricing. Gemini 3 Pro costs $1.25/1M input and $5/1M 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 Gemini 3 Pro or GLM-5 open source?
Gemini 3 Pro is listed under Proprietary. 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 vision, Gemini 3 Pro or GLM-5?
Gemini 3 Pro has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Gemini 3 Pro or GLM-5?
Gemini 3 Pro has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemini 3 Pro and GLM-5?
Gemini 3 Pro is available on Replicate API 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.
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Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.