LLM Reference

GLM-5 vs o3

GLM-5 (2026) and o3 (2025) are frontier-tier reasoning models from Zhipu AI and OpenAI. GLM-5 ships a 200k-token context window, while o3 ships a 200k-token context window. On SWE-bench Verified, GLM-5 leads by 6.1 pts. On pricing, GLM-5 costs $0.60/1M input tokens versus $2/1M 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 ~233% cheaper at $0.60/1M; pay for o3 only for coding workflow support.

Decision scorecard

Local evidence first
SignalGLM-5o3
Best forreasoning-heavy apps, tool-calling agents, and provider-routed productionreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window200k200k
Cheapest output$2.08/1M tokens$8/1M tokens
Provider routes7 tracked3 tracked
Shared benchmarksSWE-bench Verified leader5 rows

Decision tradeoffs

Choose GLM-5 when...
  • GLM-5 holds a shared-benchmark lead on SWE-bench Verified, ahead by 6.1 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.
Choose o3 when...
  • o3 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 1.7 points.
  • o3 uniquely exposes Vision, Multimodal, and Code execution in local model data.
  • Local decision data tags o3 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

GLM-5

$1,000

Cheapest tracked route/tier: OpenRouter

o3

$3,600

Cheapest tracked route/tier: OpenAI API

Estimated monthly gap: $2,600. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GLM-5 -> o3
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • o3 is $5.92/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • o3 adds Vision, Multimodal, and Code execution in local capability data.
o3 -> GLM-5
  • Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
  • GLM-5 is $5.92/1M 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.

Specs

Specification
Released2026-02-112025-04-16
Context window200k200k
Parameters744B total, 40B active
Architecturemixture of expertsdecoder only
LicenseMIT(OSI)Proprietary
OpennessOpen sourceProprietary
Commercial useCommercial use allowedCommercial use with conditions
Knowledge cutoff2025-112024-06

Pricing and availability

Pricing attributeGLM-5o3
Input price$0.60/1M tokens$2/1M tokens
Output price$2.08/1M tokens$8/1M tokens
Providers

Capabilities

CapabilityGLM-5o3
VisionNoYes
MultimodalNoYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionNoYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGLM-5o3
SWE-bench Verified77.871.7
Google-Proof Q&A86.087.7
AIME 202592.788.9
LiveCodeBench81.985.5
Humanity's Last Exam30.520.3

Deep dive

On shared benchmark coverage, SWE-bench Verified has GLM-5 at 77.8 and o3 at 71.7, with GLM-5 ahead by 6.1 points; Google-Proof Q&A has GLM-5 at 86 and o3 at 87.7, with o3 ahead by 1.7 points; AIME 2025 has GLM-5 at 92.7 and o3 at 88.9, with GLM-5 ahead by 3.8 points. The largest visible gap is 6.1 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: o3, multimodal input: o3, and code execution: o3. 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, GLM-5 lists $0.60/1M input and $2.08/1M output tokens on the cheapest tracked provider, while o3 lists $2/1M input and $8/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GLM-5 lower by about $2.76 per million blended tokens. Availability is 7 providers versus 3, so concentration risk also matters.

Choose GLM-5 when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose o3 when coding workflow support 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, GLM-5 or o3?

GLM-5 supports 200k tokens, while o3 supports 200k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is cheaper, GLM-5 or o3?

GLM-5 is cheaper on tracked token pricing. GLM-5 costs $0.60/1M input and $2.08/1M output tokens. o3 costs $2/1M input and $8/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GLM-5 or o3 open source?

GLM-5 is listed under MIT. o3 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, GLM-5 or o3?

o3 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, GLM-5 or o3?

o3 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 GLM-5 and o3?

GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. o3 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-08. Data sourced from public model cards and provider documentation.