Qwen3.8-27B vs DeepSeek-V4-Flash-Vision-Exp
Why this pair: Open-weight multimodal models from DeepSeek and Qwen
Benchmark Performance
Available Benchmarks
| Benchmark | Qwen3.8-27B | DeepSeek-V4-Flash-Vision-Exp |
|---|---|---|
| LiveBench2026-06-25 · overall · leader | 78.0298% of row best · percent · qwen3.8-27b · 28,740 output tokens / case | 79.67100% of row best · percent · deepseek-v4-flash-vision-exp · 52,644 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 1 benchmark winOverall lead |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Technical Differences
Side-by-Side Facts
| Field | Qwen3.8-27B | DeepSeek-V4-Flash-Vision-Exp |
|---|---|---|
| Developer | Qwen | DeepSeek |
| Family | Qwen3 8 27b | Deepseek V4 Flash Vision Exp |
| Model | Qwen3.8-27B | DeepSeek-V4-Flash-Vision-Exp |
| Version | Qwen3.8-27B | DeepSeek-V4-Flash-Vision-Exp |
| Lifecycle | active | preview |
| Released | Unknown | 2026-08-21 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 262,144 | 1,048,576 |
| Total parameters | 27,781,427,952 | 304,646,824,126 |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Openrouter (Standard) | DeepSeek (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
15 comparable fields · 10 material differences · Editorially curated pair passes the primary-source comparison gate
Qwen3.8-27B Capabilities
DeepSeek-V4-Flash-Vision-Exp Capabilities
Internal Comparison Graph
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
DeepSeek-V4-FlashDeepSeek | vs | DeepSeek-V4-Flash-Vision-ExpDeepSeek | family variantstext |
DeepSeek-V4-Flash-Vision-ExpDeepSeek | vs | DeepSeek-V4-ProDeepSeek | family variantstext |
DeepSeek-V4-Flash-Vision-ExpDeepSeek | vs |  GLM-5.3-FlashZ.ai | cross-developer peersimage, text |
DeepSeek-V4-Flash-Vision-ExpDeepSeek | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs | DeepSeek-V4-Flash-Vision-ExpDeepSeek | cross-developer peersimage, text |
Qwen3.5-35B-A3BQwen | vs | Qwen3.8-27BQwen | family variantsimage, text |
| vs | Qwen3.8-27BQwen | family variantsimage, text | |
| vs | Qwen3.8-27BQwen | family variantsimage, text | |
DeepSeek-V4-Flash-Vision-ExpDeepSeek | vs | Qwen3.8-MaxQwen | cross-developer peersimage, text |
DeepSeek-V4-Flash-Vision-ExpDeepSeek | vs | Qwen3.7-PlusQwen | cross-developer peersimage, text |
Qwen3.8-27BQwen | vs |  Ministral-3-14B-Reasoning-2512Mistral AI | cross-developer peersimage, text |
Qwen3.8-27BQwen | vs | Ministral-3-8B-Reasoning-2512Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Qwen3.8-27B vs DeepSeek-V4-Flash-Vision-Exp FAQs
Is Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.8-27B and DeepSeek-V4-Flash-Vision-Exp, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp?+
Qwen3.8-27B is $0.40 and DeepSeek-V4-Flash-Vision-Exp is $0.22 per million tokens, so DeepSeek-V4-Flash-Vision-Exp is cheaper on this metric. Qwen3.8-27B is $2.55 and DeepSeek-V4-Flash-Vision-Exp is $0.66 per million tokens, so DeepSeek-V4-Flash-Vision-Exp is cheaper on this metric.
Which has a larger context window, Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp?+
DeepSeek-V4-Flash-Vision-Exp has the larger sourced context window. Qwen3.8-27B supports 262,144 and DeepSeek-V4-Flash-Vision-Exp supports 1,048,576.
Which performs better in benchmarks, Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.8-27B is open weight; DeepSeek-V4-Flash-Vision-Exp is open weight.
Can Qwen3.8-27B and DeepSeek-V4-Flash-Vision-Exp understand images?+
Qwen3.8-27B is documented with image input; DeepSeek-V4-Flash-Vision-Exp is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp?+
DeepSeek-V4-Flash-Vision-Exp has the larger sourced maximum output: Qwen3.8-27B supports 131,072 and DeepSeek-V4-Flash-Vision-Exp supports 393,216 output tokens.
Do Qwen3.8-27B and DeepSeek-V4-Flash-Vision-Exp support reasoning and tool use?+
Qwen3.8-27B: reasoning, tool calling, and image input. DeepSeek-V4-Flash-Vision-Exp: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp?+
Qwen3.8-27B has 2 sourced provider routes; DeepSeek-V4-Flash-Vision-Exp has 1, so Qwen3.8-27B has broader tracked availability.
Which offers better value, Qwen3.8-27B or DeepSeek-V4-Flash-Vision-Exp?+
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.