Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Gemini 3 Flash Preview (Non-reasoning) | Qwen3.8 27B (low) |
|---|---|---|
| Input ($/M tokens) | $0.5 | $0.5 |
| Output ($/M tokens) | $3 | $3 |
Verdict. Qwen3.8 27B (low) takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Qwen3.8 27B (low) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen3.8 27B (low) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Gemini 3 Flash Preview (Non-reasoning) is strongest on Intelligence Index (27.9). Qwen3.8 27B (low) leads on Coding Index (58.2), Intelligence Index (42.9).
Speed. On throughput, Gemini 3 Flash Preview (Non-reasoning) generates tokens at 195 tok/s versus 65 tok/s — about 66% faster. On time-to-first-token, Gemini 3 Flash Preview (Non-reasoning) responds in 730ms vs 2990ms, which matters most for chat-style UIs.
Provider. Google and Alibaba sell to overlapping but distinct developer audiences: Google 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): Gemini 3 Flash Preview (Non-reasoning) costs $60.00 ($720/year); Qwen3.8 27B (low) costs $60.00 ($720/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Gemini 3 Flash Preview (Non-reasoning) ≈ $8.50/run, Qwen3.8 27B (low) ≈ $8.50/run. At agent/realtime scale (200M input / 100M output per million requests): Gemini 3 Flash Preview (Non-reasoning) ≈ $400/run, Qwen3.8 27B (low) ≈ $400/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.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
Qwen3.8 27B (low) wins 2 out of 12 benchmarks compared to 0 for Gemini 3 Flash Preview (Non-reasoning). See the detailed benchmark chart above for per-category results.
Gemini 3 Flash Preview (Non-reasoning) generates tokens faster at 195 tok/s vs 65 tok/s. Gemini 3 Flash Preview (Non-reasoning) also has lower time-to-first-token (0.73s vs 2.99s).
Choose based on your priorities: both are similarly priced, Qwen3.8 27B (low) for stronger benchmark performance, and Gemini 3 Flash Preview (Non-reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.