Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Qwen3.8 27B | GLM-5 (Reasoning) |
|---|---|---|
| Input ($/M tokens) | $0.45 | $1 |
| Output ($/M tokens) | $3.2 | $3.2 |
Verdict. Qwen3.8 27B 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, GLM-5 (Reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GLM-5 (Reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Qwen3.8 27B is strongest on Coding Index (68.1), Intelligence Index (52.0). GLM-5 (Reasoning) leads on Intelligence Index (40.6).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Alibaba and Z AI sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while Z AI 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): Qwen3.8 27B costs $61.50 ($738/year); GLM-5 (Reasoning) costs $78.00 ($936/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3.8 27B ≈ $8.65/run, GLM-5 (Reasoning) ≈ $11.40/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3.8 27B ≈ $410/run, GLM-5 (Reasoning) ≈ $520/run. Qwen3.8 27B becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
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
Qwen3.8 27B is cheaper overall. Its blended price (3:1 input/output ratio) is $1.14/M tokens vs $1.55/M for GLM-5 (Reasoning).
Qwen3.8 27B wins 2 out of 12 benchmarks compared to 0 for GLM-5 (Reasoning). See the detailed benchmark chart above for per-category results.
GLM-5 (Reasoning) generates tokens faster at 46 tok/s vs — tok/s. However, GLM-5 (Reasoning) has lower time-to-first-token (1.71s vs —s).
Choose based on your priorities: Qwen3.8 27B for lower cost, Qwen3.8 27B for stronger benchmark performance, and GLM-5 (Reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.