Qwen3.8 2.4T A95B vs DeepSeek V4.1 Flash
At a Glance
| Compare |  DeepSeek V4.1 FlashDeepSeek | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #5 of 44$0.022 per LiveBench case |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $2.00Deepinfra ↗ · Sep 21, 2026 | $0.15DeepSeek ↗ · Sep 10, 2026 |
| Output priceFrom · USD / 1M tokens | $6.00Deepinfra ↗ · Sep 21, 2026 | $0.60Deepinfra ↗ · Sep 21, 2026 |
| Context windowMaximum documented tokens | 262K | 1,049K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 10, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Qwen3.8-2.4T-A95B | DeepSeek-V4.1-Flash |
|---|---|---|
| Developer | Qwen | DeepSeek |
| Family | Qwen3 8 2 4t A95b | Deepseek V4 1 |
| Model | Qwen3.8-2.4T-A95B | DeepSeek-V4.1-Flash |
| Version | Qwen3.8-2.4T-A95B | DeepSeek-V4.1-Flash |
| Lifecycle | active | active |
| Released | Unknown | 2026-09-10 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 262K | 1,049K |
| Total parameters | 2.4T | 763.2B |
| Active parameters | 95B | Unknown |
| License | other | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | DeepSeek (Standard), Deepinfra (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | agents, chat, fim, generation, reasoning, responses, structured_outputs, tools, vision |
| Architecture design | Unknown | Causal Encoder-Decoder (20 encoder + 20 decoder layers) |
| Backbone parameters | Unknown | 552000000000 parameters |
| Active parameters during decode | Unknown | 16000000000 parameters |
| Active parameters during prefill | Unknown | 8000000000 parameters |
| Pre-training corpus | Unknown | 45000000000000 tokens |
| Reasoning effort range | Unknown | 1–100 |
| Routed experts per MoE layer | Unknown | 384 experts |
| Routed experts per token | Unknown | 6 experts |
| Transformer layers | Unknown | 40 layers |
Qwen3.8 2.4T A95B Capabilities
DeepSeek V4.1 Flash Capabilities
Related Comparisons
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|---|---|---|---|
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| vs |  GPT-6 AstraOpenAI | cross-developer peerstext | |
| vs | Claude Fable 5.1Anthropic | cross-developer peerstext | |
| vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext | |
| vs | Grok 4.6xAI | cross-developer peerstext | |
| vs |  Qwen3.8-MaxQwen | family variantstext | |
| vs |  Kimi-K3Moonshot AI | cross-developer peerstext | |
 MiniMax-M3MiniMax | vs | cross-developer peerstext | |
| vs |  GLM-5.3Z.ai | cross-developer peerstext | |
| vs |  Hy4 previewTencent | cross-developer peerstext | |
| vs | Seed 2.1 ProByteDance Seed | cross-developer peerstext | |
| vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Qwen3.8 2.4T A95B vs DeepSeek V4.1 Flash FAQs
Is Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8 2.4T A95B and DeepSeek V4.1 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash?+
Qwen3.8 2.4T A95B is $2.00 and DeepSeek V4.1 Flash is $0.15 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric. Qwen3.8 2.4T A95B is $6.00 and DeepSeek V4.1 Flash is $0.60 per million tokens, so DeepSeek V4.1 Flash is cheaper on this metric.
Which has a larger context window, Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash?+
DeepSeek V4.1 Flash has the larger sourced context window. Qwen3.8 2.4T A95B supports 262K and DeepSeek V4.1 Flash supports 1,049K.
Which performs better in benchmarks, Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.8 2.4T A95B is open weight; DeepSeek V4.1 Flash is open weight.
Can Qwen3.8 2.4T A95B and DeepSeek V4.1 Flash understand images?+
Qwen3.8 2.4T A95B is not documented with image input; DeepSeek V4.1 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash?+
Neither has a larger sourced maximum output. Qwen3.8 2.4T A95B is — and DeepSeek V4.1 Flash is 393K.
Do Qwen3.8 2.4T A95B and DeepSeek V4.1 Flash support reasoning and tool use?+
Qwen3.8 2.4T A95B: reasoning and tool calling. DeepSeek V4.1 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash?+
Qwen3.8 2.4T A95B has 5 sourced provider routes; DeepSeek V4.1 Flash has 3, so Qwen3.8 2.4T A95B has broader tracked availability.
Which offers better value, Qwen3.8 2.4T A95B or DeepSeek V4.1 Flash?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.