Claude Opus 4.8 vs GLM-5.2
Claude Opus 4.8 (2026) and GLM-5.2 (2026) are frontier-tier reasoning models from Anthropic and Zhipu AI. Claude Opus 4.8 ships a 1m-token context window, while GLM-5.2 ships a 1m-token context window. On SWE-bench Pro, Claude Opus 4.8 leads by 7.1 pts. On pricing, GLM-5.2 costs $1.40/1M 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-5.2 is ~257% cheaper at $1.40/1M; pay for Claude Opus 4.8 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Claude Opus 4.8 | GLM-5.2 |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | reasoning-heavy apps, tool-calling agents, and long-context analysis |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 1m |
| Cheapest output | $25/1M tokens | $4.40/1M tokens |
| Provider routes | 6 tracked | 1 tracked |
| Shared benchmarks | SWE-bench Pro leader | 11 shared |
Decision tradeoffs
- Claude Opus 4.8 holds a shared-benchmark lead on SWE-bench Pro, ahead by 7.1 points.
- Claude Opus 4.8 has broader tracked provider coverage for fallback and route flexibility.
- Claude Opus 4.8 uniquely exposes Vision, Multimodal, and Computer use in local model data.
- Local decision data tags Claude Opus 4.8 for Coding, RAG, and Agents.
- GLM-5.2 holds a shared-benchmark lead on Terminal-Bench 2.1, ahead by 8.1 points.
- GLM-5.2 has the lower cheapest tracked output price at $4.40/1M tokens.
- Local decision data tags GLM-5.2 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 4.8
$10,250
Cheapest tracked route/tier: Anthropic
GLM-5.2
$2,220
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $8,030. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GLM-5.2 is $20.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Computer use before moving production traffic.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Claude Opus 4.8 is $20.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Claude Opus 4.8 adds Vision, Multimodal, and Computer use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-05-28 | 2026-06-13 |
| Context window | 1m | 1m |
| Parameters | — | 753B total, 40B active |
| Architecture | Decoder Only | Mixture of Experts |
| License | Proprietary | MITOSI-approved |
| Openness | Proprietary | Open source |
| Weights | Not released | Available |
| Code | Not released | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2026-01 | - |
Pricing and availability
| Pricing attribute | Claude Opus 4.8 | GLM-5.2 |
|---|---|---|
| Input price | $5/1M tokens | $1.40/1M tokens |
| Output price | $25/1M tokens | $4.40/1M tokens |
| Providers |
Capabilities
| Capability | Claude Opus 4.8 | GLM-5.2 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | Yes |
| JSON / Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | Yes | No |
| Parallel agents | Yes | No |
Benchmarks
| Benchmark | Claude Opus 4.8 | GLM-5.2 |
|---|---|---|
| SWE-bench Pro | 69.2 | 62.1 |
| Google-Proof Q&A | 93.6 | 91.2 |
| Terminal-Bench 2.1 | 74.6 | 82.7 |
| CursorBench | 63.8 | 51.5 |
| GeneBench-Pro | 16.0 | 4.6 |
| CursorBench | 62.3 | 51.5 |
| CursorBench | 59.4 | 51.5 |
| CursorBench | 58.0 | 51.5 |
| MCP-Atlas | 82.2 | 76.8 |
| CursorBench | 56.1 | 51.5 |
| CursorBench | 53.1 | 51.5 |
Continue comparing
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Last reviewed: 2026-07-26. Data sourced from public model cards and provider documentation.