Gemini 2.5 Pro vs GLM-5
Gemini 2.5 Pro (2025) and GLM-5 (2026) are frontier-tier reasoning models from Google DeepMind and Zhipu AI. Gemini 2.5 Pro ships a 1m-token context window, while GLM-5 ships a 200k-token context window. On MMLU PRO, Gemini 2.5 Pro leads by 0.2 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Gemini 2.5 Pro fits 5x more tokens; pick it for long-context work and GLM-5 for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | 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 | $10/1M tokens | $2.08/1M tokens |
| Provider routes | 4 tracked | 7 tracked |
| Shared benchmarks | MMLU PRO leader | 6 rows |
Decision tradeoffs
- Gemini 2.5 Pro holds a shared-benchmark lead on MMLU PRO, ahead by 0.2 points.
- Gemini 2.5 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 2.5 Pro uniquely exposes Vision, Multimodal, and Code execution in local model data.
- Local decision data tags Gemini 2.5 Pro for Coding, RAG, and Agents.
- GLM-5 holds a shared-benchmark lead on SWE-bench Verified, ahead by 14 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.
- 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 2.5 Pro
$3,500
Cheapest tracked route/tier: Google AI Studio <=200K tokens
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $2,500. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, GCP Vertex AI, and Vercel AI Gateway; start route-level A/B tests there.
- GLM-5 is $7.92/1M 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.
- Provider overlap exists on GCP Vertex AI, OpenRouter, and Vercel AI Gateway; start route-level A/B tests there.
- Gemini 2.5 Pro is $7.92/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Gemini 2.5 Pro adds Vision, Multimodal, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-17 | 2026-02-11 |
| Context window | 1m | 200k |
| Parameters | — | 744B total, 40B active |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | MIT(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-01 | 2025-11 |
Pricing and availability
| Pricing attribute | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| Input price |
| $0.60/1M tokens |
| Output price |
| $2.08/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemini 2.5 Pro | GLM-5 |
|---|---|---|
| MMLU PRO | 86.2 | 86.0 |
| SWE-bench Verified | 63.8 | 77.8 |
| Google-Proof Q&A | 86.4 | 86.0 |
| AIME 2025 | 86.7 | 92.7 |
| LiveCodeBench | 75.6 | 81.9 |
| Humanity's Last Exam | 18.8 | 30.5 |
Deep dive
On shared benchmark coverage, MMLU PRO has Gemini 2.5 Pro at 86.2 and GLM-5 at 86, with Gemini 2.5 Pro ahead by 0.2 points; SWE-bench Verified has Gemini 2.5 Pro at 63.8 and GLM-5 at 77.8, with GLM-5 ahead by 14 points; Google-Proof Q&A has Gemini 2.5 Pro at 86.4 and GLM-5 at 86, with Gemini 2.5 Pro ahead by 0.4 points. The largest visible gap is 14 points on SWE-bench Verified, 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 2.5 Pro, multimodal input: Gemini 2.5 Pro, and code execution: Gemini 2.5 Pro. Both models share reasoning mode, function calling, tool use, and 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, Gemini 2.5 Pro lists tiered pricing: <=200K tokens is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output, 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 $2.83 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 4 providers versus 7, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support and larger context windows are central to the workload. Choose GLM-5 when provider fit, 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 2.5 Pro or GLM-5?
Gemini 2.5 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 2.5 Pro or GLM-5?
Gemini 2.5 Pro lists tiered pricing: <=200K tokens is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output. GLM-5 lists $0.60/1M input and $2.08/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or GLM-5 open source?
Gemini 2.5 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 2.5 Pro or GLM-5?
Gemini 2.5 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 2.5 Pro or GLM-5?
Gemini 2.5 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 2.5 Pro and GLM-5?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, OpenRouter, and Vercel AI Gateway. 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: 2026-06-05. Data sourced from public model cards and provider documentation.