Laguna M.1 vs GLM 4.7 Flash
Detailed technical comparison between Laguna M.1 (Poolside) and GLM 4.7 Flash (Zhipu AI). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.
Comparison Snapshot
Laguna M.1
262,144 tokensTie
Equal CapabilityTie
Equal SpeedGLM 4.7 Flash
$0.06 / MTokLaguna M.1
Laguna M.1 is the flagship coding agent model from [Poolside](https://poolside.ai/), optimized for complex software engineering tasks. Designed for agentic coding workflows, it supports tool calling and reasoning, with a 256K...
GLM 4.7 Flash
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...
Technical Specifications
🏆 = Superior Spec| Specification | Laguna M.1 | GLM 4.7 Flash |
|---|---|---|
| Provider | Poolside | Zhipu AI |
| Context Window | 262,144 tokens🏆 | 202,752 tokens |
| Agent Suitability | Not yet benchmarked | Not yet benchmarked |
| Time to First Token (TTFT) | No public TTFT data | No public TTFT data |
| Deployment Model | managed api | managed api |
| Production Stability | Stable GA (est.) | Stable GA (est.) |
| API Available | Yes | Yes |
| Released Date | 2026-04-28 | 2026-01-19 |
API Pricing Comparison
Input Price per Million Tokens
Laguna M.1
$0.20
GLM 4.7 Flash
$0.06
Output Price per Million Tokens
Laguna M.1
$0.40
GLM 4.7 Flash
$0.40
💡 Cost Ratio: GLM 4.7 Flash is 3.3x cheaper per input token than Laguna M.1.
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Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Standardized Scores (0–100%)Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.
Laguna M.1 Quirks & Gotchas
No developer gotchas reported.
GLM 4.7 Flash Quirks & Gotchas
No developer gotchas reported.
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