LLM Reference

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
SignalGemini 2.5 ProGLM-5
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsreasoning-heavy apps, tool-calling agents, and provider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1m200k
Cheapest output$10/1M tokens$2.08/1M tokens
Provider routes4 tracked7 tracked
Shared benchmarksMMLU PRO leader6 shared

Decision tradeoffs

Choose Gemini 2.5 Pro when...
  • 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.
Choose GLM-5 when...
  • 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 route 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.

Lower estimate GLM-5

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

Gemini 2.5 Pro -> GLM-5
  • 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.
GLM-5 -> Gemini 2.5 Pro
  • 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
Released2025-06-172026-02-11
Context window1m200k
Parameters744B total, 40B active
ArchitectureDecoder OnlyMixture of Experts
LicenseProprietaryMITOSI-approved
OpennessProprietaryOpen source
WeightsNot releasedAvailable
CodeUnknownUnknown
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff2025-012025-11

Pricing and availability

Pricing attributeGemini 2.5 ProGLM-5
Input price
<=200K tokens
$1.25/1M tokens
Standard Gemini 2.5 Pro pricing for prompts up to 200K tokens.
>200K tokens
$2.50/1M tokens
Higher Gemini 2.5 Pro tier for prompts above 200K tokens.
$0.60/1M tokens
Output price
<=200K tokens
$10/1M tokens
Standard Gemini 2.5 Pro pricing for prompts up to 200K tokens.
>200K tokens
$15/1M tokens
Higher Gemini 2.5 Pro tier for prompts above 200K tokens.
$2.08/1M tokens
Providers

Capabilities

CapabilityGemini 2.5 ProGLM-5
VisionYesNo
MultimodalYesNo
ReasoningYesYes
JSON / Tool useYesYes
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGemini 2.5 ProGLM-5
MMLU PRO86.286.0
SWE-bench Verified63.877.8
Google-Proof Q&A86.486.0
AIME 202586.792.7
LiveCodeBench75.681.9
Humanity's Last Exam18.830.5

Continue comparing

Last reviewed: 2026-06-30. Data sourced from public model cards and provider documentation.