Claude Opus 4.6 vs GLM-5
Claude Opus 4.6 (2026) and GLM-5 (2026) are frontier-tier reasoning models from Anthropic and Zhipu AI. Claude Opus 4.6 ships a 1m-token context window, while GLM-5 ships a 200k-token context window. On MMLU PRO, Claude Opus 4.6 leads by 3.1 pts. On pricing, GLM-5 costs $0.60/1M input tokens versus $5/1M 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 ~733% cheaper at $0.60/1M; pay for Claude Opus 4.6 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Claude Opus 4.6 | 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 | $25/1M tokens | $2.08/1M tokens |
| Provider routes | 6 tracked | 7 tracked |
| Shared benchmarks | MMLU PRO leader | 9 shared |
Decision tradeoffs
- Claude Opus 4.6 holds a shared-benchmark lead on MMLU PRO, ahead by 3.1 points.
- Claude Opus 4.6 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Claude Opus 4.6 uniquely exposes Vision, Multimodal, and Code execution in local model data.
- Local decision data tags Claude Opus 4.6 for Coding, RAG, and Agents.
- GLM-5 holds a shared-benchmark lead on SWE-bench Pro, ahead by 1.7 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.
Claude Opus 4.6
$10,250
Cheapest tracked route/tier: Anthropic
GLM-5
$1,000
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $9,250. 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 $22.92/1M 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.
- Claude Opus 4.6 is $22.92/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Claude Opus 4.6 adds Vision, Multimodal, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-05 | 2026-02-11 |
| Context window | 1m | 200k |
| Parameters | — | 744B total, 40B active |
| Architecture | Decoder Only | Mixture of Experts |
| License | Proprietary | MITOSI-approved |
| Openness | Proprietary | Open source |
| Weights | Not released | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2025-12 | 2025-11 |
Pricing and availability
| Pricing attribute | Claude Opus 4.6 | GLM-5 |
|---|---|---|
| Input price | $5/1M tokens | $0.60/1M tokens |
| Output price | $25/1M tokens | $2.08/1M tokens |
| Providers |
Capabilities
| Capability | Claude Opus 4.6 | GLM-5 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | Yes |
| JSON / 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 | Claude Opus 4.6 | GLM-5 |
|---|---|---|
| MMLU PRO | 89.1 | 86.0 |
| SWE-bench Verified | 80.8 | 77.8 |
| SWE-bench Pro | 53.4 | 55.1 |
| Google-Proof Q&A | 91.3 | 86.0 |
| AIME 2025 | 94.2 | 92.7 |
| LiveCodeBench | 70.2 | 81.9 |
| Humanity's Last Exam | 53.0 | 30.5 |
| τ-bench | 84.8 | 82.1 |
| SWE-rebench | 65.3 | 62.8 |
Continue comparing
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Last reviewed: 2026-07-26. Data sourced from public model cards and provider documentation.