Claude Sonnet 5.5 vs GLM-5.3
Claude Sonnet 5.5 scores higher on the Models at Work leaderboard (86 vs 81 out of 100). GLM-5.3 is about 1.9× cheaper per blended million tokens ($2.15 vs $4). On Artificial Analysis' independent Intelligence Index, Claude Sonnet 5.5 leads 56 to 45.
| Claude Sonnet 5.5 · Anthropic | GLM-5.3 · Z.ai | |
|---|---|---|
| Leaderboard rank | #1 | #5 |
| Score (0–100) | 86 | 81 |
| Tier | Workhorse | Open weights |
| Price per 1M tokens | $2 in · $10 out | $1.40 in · $4.40 out |
| Context window | 1M | 1M |
| Open weights | No | Yes |
| Artificial Analysis Intelligence Index | 56 | 45 |
| Arena Text score | — | 1478 (rank 27) |
| Scale SWE-Bench Pro V2 (mini-swe-agent) | — | 84.30% |
| Scale MCP Atlas | — | 84.20 |
| Arena WebDev score | — | 1622 (rank 22) |
| Best for | Production coding assistants, High-volume agents, Default model for most teams | Agentic coding in Claude Code / Pi-style harnesses, Security research and code auditing, Self-hosted frontier-ish reasoning |
Choose Claude Sonnet 5.5 if…
- you need production coding assistants
- you need high-volume agents
- you need default model for most teams
The value pick of the table: second on the index at a fifth of the Opus price, and the fastest of the top five.
Choose GLM-5.3 if…
- you need agentic coding in claude code / pi-style harnesses
- you need security research and code auditing
- you need self-hosted frontier-ish reasoning
The open model people actually ship coding agents on. Same 744B base as GLM-5.2 with heavy agentic post-training; drops into Claude Code harnesses and holds its own on SWE-Bench Pro V2 and MCP Atlas at a third of frontier prices.
Caveats: License is muddled: AA lists a custom 'GLM-5.3 License' with commercial restrictions while Arena lists MIT. Read it before you self-host. Permissive on offensive-security tasks; that is a feature for red teams and a governance problem for everyone else. Open weights shipped ~2 weeks after the API; HN worried the public weights were safety-tuned differently.
What practitioners say
Claude Sonnet 5.5: Less discussed than its siblings because it just works; the October cache-read price cut to $0.10 per million was the news.
GLM-5.3: One of the biggest HN launches of the year (1,171 points, 584 comments). Practitioners report it 'fits Claude Code as its own, zero issues', that '$5 in tokens' of Claude work costs '$0.50' on GLM via Pi, and that it 'routinely finds bugs missed by Fable and Sol' in audits. The cyber angle was the controversy: users bragged about adapting kernel exploits that 'Claude and Opus outright refused', and others flagged the risk of nerfed public weights.
Questions people ask
Which is better, Claude Sonnet 5.5 or GLM-5.3?
Claude Sonnet 5.5 scores higher on the Models at Work leaderboard (86 vs 81 out of 100). GLM-5.3 is about 1.9× cheaper per blended million tokens ($2.15 vs $4). On Artificial Analysis' independent Intelligence Index, Claude Sonnet 5.5 leads 56 to 45.
When should I choose Claude Sonnet 5.5 over GLM-5.3?
Choose Claude Sonnet 5.5 for production coding assistants, high-volume agents, default model for most teams. The value pick of the table: second on the index at a fifth of the Opus price, and the fastest of the top five.
When should I choose GLM-5.3 over Claude Sonnet 5.5?
Choose GLM-5.3 for agentic coding in claude code / pi-style harnesses, security research and code auditing, self-hosted frontier-ish reasoning. The open model people actually ship coding agents on. Same 744B base as GLM-5.2 with heavy agentic post-training; drops into Claude Code harnesses and holds its own on SWE-Bench Pro V2 and MCP Atlas at a third of frontier prices.
Which is cheaper, Claude Sonnet 5.5 or GLM-5.3?
Claude Sonnet 5.5 costs $2 per million input tokens and $10 per million output tokens on Anthropic's list price (Claude pricing, read Oct 11, 2026). GLM-5.3 costs $1.40 per million input tokens and $4.40 per million output tokens on Z.ai's list price (Z.ai Pricing, read Oct 11, 2026).
Scores come from the Models at Work leaderboard: Score is 0 to 100 and computed, not typed: 55% independent evals (Artificial Analysis, Arena, Scale SEAL, Epoch, each scaled against its natural floor and the best score in this table, then averaged), 15% blended price on a fixed log scale ($0.05 per million is 100, $60 is 0), 15% practitioner sentiment from Signals and community threads, 15% operational fit (context window, open weights). A missing component drops out and the rest are reweighted. A model with no independent eval yet is provisional and ranks below every measured one. Within three points is a tie. Vendor-published figures are labelled and never counted. Prices are vendor list prices where published; blended figures assume three input tokens per output token.