DeepSeek V4.1 Flash vs Qwen3.8 Max vs Ling-3.0-flash-Fin: The 2026 Flash-Model Price War
Direct answer
Three flash-class models dropped within days of each other in September 2026, and they split cleanly by price. DeepSeek V4.1 Flash costs $0.15 in / $0.60 out per 1M tokens and scores 40 on the Artificial Analysis Intelligence Index; Qwen3.8 Max (0902) costs $2.00 / $6.00 and scores 45; Ant Group’s Ling-3.0-flash-Fin is a finance-tuned entrant. [ E5 Artificial Analysis; E5 OrcaRouter] For most agent and drafting workloads, DeepSeek’s 20x lower cost-per-task wins; Qwen’s premium buys hard-reasoning and video input.
The numbers, side by side
| Model | In / Out ($/1M) | Intelligence Index | Context | Standout |
|---|---|---|---|---|
| DeepSeek V4.1 Flash | 0.15 / 0.60 (off-peak cached $0.003 in) | 40 | 1M | Throughput 214 t/s, TTFT 783ms [ E5] |
| Qwen3.8 Max (0902) | 2.00 / 6.00 | 45 | 1M | Video input, 2.4T params [ E5] |
| Ling-3.0-flash-Fin | not disclosed | finance-tuned | — | Ant Group, finance focus [ E5] |
Cost per Intelligence Index task tells the real story: DeepSeek lands at $0.27 vs Qwen’s $5.41 — a 20x gap for a five-point index difference. [ E5 OrcaRouter]
What you actually get for the premium
Qwen3.8-Max is the bigger model by far: 2.4 trillion parameters, ~95B active per token, versus DeepSeek’s 552B total / 8–16B active. [ E5 OrcaRouter] Alibaba’s launch table claims 92.6 on GPQA Diamond and first place on OSWorld-Verified — vendor-reported, unreproduced. [ E3 Alibaba] Independent reads put Qwen ahead on closed-form hard reasoning (GPQA 92.7 vs DeepSeek’s 90.9). [ E5 OrcaRouter] So the premium is real but narrow: hard science, plus the video input DeepSeek lacks.
Where DeepSeek wins
- Agent loops. Its 98% cache discount ($0.003/1M cached input) makes repeated codebase and document reads cheap. [ E5 OrcaRouter; E3 DeepSeek]
- Speed. 214 tokens/sec and ~0.8s to first token vs Qwen’s ~10s. [ E5]
- Bulk drafting. For high-volume generation, the bill is a fraction. [ E1]
Where Ling-3.0-flash-Fin fits
Ant Group built Ling-3.0-flash-Fin for finance workflows — the kind of domain-tuned flash model we’ll likely see more of. Pricing wasn’t public at write time; treat any number as needs_check until Artificial Analysis posts a full eval. [ E5 Artificial Analysis; E1]
Verdict
Pick DeepSeek V4.1 Flash as your default for agents and volume; reach for Qwen3.8 Max when the task is hard reasoning or needs video. [ E1] Ling-3.0-flash-Fin is one to watch for finance teams. None of these justifies a scored star rating in structured data — we’re comparing vendor and benchmark numbers, not user ratings.
FAQ
Which is cheaper, DeepSeek V4.1 Flash or Qwen3.8 Max? DeepSeek, by roughly 20x per Intelligence Index task ($0.27 vs $5.41). [ E5 OrcaRouter]
Does Qwen3.8 Max support video? Yes — it accepts text, image, and video input; DeepSeek V4.1 Flash is text and image. [ E5]
What is Ling-3.0-flash-Fin? Ant Group’s finance-focused flash LLM, released mid-September 2026; pricing not yet public. [ E5 Artificial Analysis]
