Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GLM-4.6 (Reasoning) | MiniMax M1 80k |
|---|---|---|
| Input ($/M tokens) | $0.55 | $0.55 |
| Output ($/M tokens) | $2.2 | $2.2 |
Verdict. GLM-4.6 (Reasoning) wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, MiniMax M1 80k is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). MiniMax M1 80k makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GLM-4.6 (Reasoning) is strongest on Coding Index (45.8), Intelligence Index (29.3). MiniMax M1 80k leads on Intelligence Index (17.9).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Z AI and MiniMax sell to overlapping but distinct developer audiences: Z AI tends to ship frontier reasoning models with premium positioning, while MiniMax often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GLM-4.6 (Reasoning) costs $49.50 ($594/year); MiniMax M1 80k costs $49.50 ($594/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GLM-4.6 (Reasoning) ≈ $7.15/run, MiniMax M1 80k ≈ $7.15/run. At agent/realtime scale (200M input / 100M output per million requests): GLM-4.6 (Reasoning) ≈ $330/run, MiniMax M1 80k ≈ $330/run.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
GLM-4.6 (Reasoning) wins 2 out of 12 benchmarks compared to 0 for MiniMax M1 80k. See the detailed benchmark chart above for per-category results.
GLM-4.6 (Reasoning) generates tokens faster at 54 tok/s vs — tok/s. GLM-4.6 (Reasoning) also has lower time-to-first-token (2.39s vs —s).
Choose based on your priorities: both are similarly priced, GLM-4.6 (Reasoning) for stronger benchmark performance, and GLM-4.6 (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.