Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GLM-5.3-Flash | Qwen2.5 Instruct 72B |
|---|---|---|
| Input ($/M tokens) | $0.15 | $0.47 |
| Output ($/M tokens) | $0.5 | $0.49 |
Verdict. GLM-5.3-Flash 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, Qwen2.5 Instruct 72B is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen2.5 Instruct 72B makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GLM-5.3-Flash is strongest on Coding Index (71.5), Intelligence Index (57.5). Qwen2.5 Instruct 72B leads on Intelligence Index (9.4).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Z AI and Alibaba sell to overlapping but distinct developer audiences: Z AI tends to ship frontier reasoning models with premium positioning, while Alibaba 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-5.3-Flash costs $12.00 ($144/year); Qwen2.5 Instruct 72B costs $21.45 ($257/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GLM-5.3-Flash ≈ $1.75/run, Qwen2.5 Instruct 72B ≈ $3.33/run. At agent/realtime scale (200M input / 100M output per million requests): GLM-5.3-Flash ≈ $80/run, Qwen2.5 Instruct 72B ≈ $143/run. GLM-5.3-Flash 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
GLM-5.3-Flash is cheaper overall. Its blended price (3:1 input/output ratio) is $0.24/M tokens vs $0.47/M for Qwen2.5 Instruct 72B.
GLM-5.3-Flash wins 2 out of 12 benchmarks compared to 0 for Qwen2.5 Instruct 72B. See the detailed benchmark chart above for per-category results.
GLM-5.3-Flash generates tokens faster at 47 tok/s vs — tok/s. GLM-5.3-Flash also has lower time-to-first-token (1.67s vs —s).
Choose based on your priorities: GLM-5.3-Flash for lower cost, GLM-5.3-Flash for stronger benchmark performance, and GLM-5.3-Flash for faster generation. For latency-sensitive apps, check the TTFT comparison above.