Model comparison
DeepSeek V3.1 vs Qwen 3.8 Flash Next
DeepSeek against Qwen, compared on context, price, and verified benchmark results.
Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
DeepSeek
DeepSeek V3.1
Budget · Open weights
Qwen
Qwen 3.8 Flash Next
Budget · Open weights
| Specification | DeepSeek V3.1 | Qwen 3.8 Flash Next |
|---|---|---|
| Provider | ||
| Provider | DeepSeek | Qwen |
| Tier | ||
| Tier | Budget | Budget |
| Context window | ||
| Context window | 128K | Winner: 262K |
| Max output | ||
| Max output | Not verifiedUnverified | Not verifiedUnverified |
| Input / 1M tokens | ||
| Input / 1M tokens | $0.25 | Winner: $0.15 |
| Output / 1M tokens | ||
| Output / 1M tokens | $0.95 | Winner: $0.47 |
| Weights | ||
| Weights | Open | Open |
| Parameters | ||
| Parameters | 671B total / 37B active (MoE) | 125B total / 6B active (MoE) + 51B n-gram embedding table |
| Reasoning levels | ||
| Reasoning levels | low, high, max | Not verifiedUnverified |
| Modalities | ||
| Modalities | text | text, image, video |
| License | ||
| License | MIT | qwen-community-1.0 |
| API model id | ||
| API model id | Not publishedUnverified | qwen3.8-flash |
| Released | ||
| Released | August 21, 2025 | August 26, 2026 |
| Artificial Analysis Intelligence Index (2026-09-26) | ||
| Artificial Analysis Intelligence Index (2026-09-26) | 13.5 | Winner: 39.8 |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
Where each score comes from, and how far it can be compared across models.
- 2026-09-26Artificial Analysis
Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.
Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.
Pricing tiers
DeepSeek V3.1: No first-party API: DeepSeek moved the deepseek-chat alias to V3.1-Terminus on 2025-09-22 (the alias itself was retired on 2026-07-24). Third-party hosts listed ~$0.25/$0.95 per MTok (secondary, last checked 2026-08-29) — verify with your host.
Qwen 3.8 Flash Next: Hosted qwen3.8-flash lists $0.15/$0.47 per MTok on Alibaba Cloud Model Studio with a 1M context. The open checkpoint is 262,144 tokens native, extensible to 1M.
DeepSeek V3.1
DeepSeek V3.1 is a legacy open-weight (MIT) 671B/37B MoE with a 128K context — superseded by V3.1-Terminus, V3.2 and then V4.
Best for
- Cost-sensitive hosted agents
- High-volume coding assist
- Open-weight deployments
Watch out
Legacy: DeepSeek's own API stopped serving V3.1 when deepseek-chat moved to V3.1-Terminus on 2025-09-22; hosted rates differ by provider and self-hosting needs datacentre VRAM.
Qwen 3.8 Flash Next
Qwen 3.8 Flash Next is Alibaba's experimental preview of the Qwen 4 architecture — very low active parameters plus an unusual n-gram embedding component for cheap long-context.
Best for
- Early testing of Qwen 4 architecture
- Cheap high-throughput work
- Multimodal input
Watch out
Experimental preview; qwen-community-1.0 license is more restrictive than MIT/Apache; benchmark claims are vendor-reported.
When the cheaper one wins
Qwen 3.8 Flash Next is cheaper on output at $0.47 per million tokens against $0.95 for DeepSeek V3.1 — about 2.0×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
How strong and complete the evidence behind this comparison is — not a prediction of which model is better.
- Pricing verified on both sides — Input and output rates are verified for both models.
- 3/5 core specs verified on both sides — Not published for at least one side: max output, reasoning levels.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- Verified within the last 90 days — Newest catalog check was 2 days ago.
- Both models carry source citations — Each side has at least two catalog sources on record.
Source receipts
Each catalog figure was checked against the provider or an independent second source on the date shown.
- DeepSeek V3.1: DeepSeek — V3.1 (accessed 2026-08-29)
- DeepSeek V3.1: CloudPrice — DeepSeek V3.1 (accessed 2026-08-29)
- DeepSeek V3.1: DeepSeek API changelog (2025-09-22: deepseek-chat upgraded to V3.1-Terminus) (accessed 2026-09-26)
- Qwen 3.8 Flash Next: The New Stack — Qwen3.8-Flash previews Qwen4 (accessed 2026-08-29)
- Qwen 3.8 Flash Next: Yotta Labs — Qwen 3.8-Flash-Next specs (accessed 2026-08-29)
- Qwen 3.8 Flash Next: Hugging Face — Qwen/Qwen3.8-Flash-Next (accessed 2026-09-26)
- Qwen 3.8 Flash Next: Alibaba Cloud Model Studio pricing (qwen3.8-flash $0.15/$0.47) (accessed 2026-09-26)
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- DeepSeek V3.1 vs DeepSeek V4 Flash
- DeepSeek V3.1 vs DeepSeek V4 Pro
Diving deeper on one model? DeepSeek V3.1 · Qwen 3.8 Flash Next
Common questions
DeepSeek V3.1 vs Qwen 3.8 Flash Next
Answered from the verified figures on this page rather than general guidance.
Is DeepSeek V3.1 or Qwen 3.8 Flash Next cheaper for input?
Is DeepSeek V3.1 or Qwen 3.8 Flash Next cheaper for output?
Which has the larger context window, DeepSeek V3.1 or Qwen 3.8 Flash Next?
Should I use DeepSeek V3.1 or Qwen 3.8 Flash Next?
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Qwen 3.8 Flash Next costs $0.15 per 1M tokens versus $0.25 for DeepSeek V3.1 — a 1.7x difference at the headline tier.
- Context: Qwen 3.8 Flash Next takes 262K against 128K for DeepSeek V3.1 — only decisive if your prompts approach the smaller window.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.