Llama 4 Scout 17B 16E Instruct vs Qwen3.8 Max
At a Glance
| Compare |  Qwen3.8 MaxQwen | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #10 of 4679.2 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 52.8–86.1 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #23 of 44$0.107 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #6 of 3863.2 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 50.0–66.7 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Deepinfra ↗ · Sep 21, 2026 | $1.65Deepinfra ↗ · Sep 21, 2026 |
| Output priceFrom · USD / 1M tokens | $0.30Deepinfra ↗ · Sep 21, 2026 | $4.951Deepinfra ↗ · Sep 21, 2026 |
| Context windowMaximum documented tokens | 10,000K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 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
| Benchmark | Llama-4-Scout-17B-16E-Instruct | Qwen3.8-Max |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,279.2986% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1274.57681953, 1284.00026285]; votes 29740; rank 259 | 1,480.55100% of row best · rating · qwen3.8-max; 95% CI [1474.79040793, 1486.31846927]; votes 16670; rank 14 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,117.8085% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1108.35603674, 1127.24229078]; votes 6466; rank 114 | 1,315.33100% of row best · rating · qwen3.8-max; 95% CI [1307.40892164, 1323.25970514]; votes 8665; rank 6 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 47.3257% of row best · points · Llama 4 Scout · 696 output tokens / case | 83.32100% of row best · points · Qwen3.8 Max · 22,888 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 2 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Llama-4-Scout-17B-16E-Instruct | Qwen3.8-Max |
|---|---|---|
| Developer | Meta | Qwen |
| Family | Llama 4 Scout 17b 16e Instruct | Qwen3 8 Max |
| Model | Llama-4-Scout-17B-16E-Instruct | Qwen3.8-Max |
| Version | Llama-4-Scout-17B-16E-Instruct | Qwen3.8-Max |
| Lifecycle | active | active |
| Released | 2025-04-05 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Video |
| Output modalities | Text | Text |
| Context window | 10,000K | 1,000K |
| Total parameters | 108.6B | 2.4T |
| Active parameters | 17B | Unknown |
| License | other | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Alibaba Cloud Model Studio (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, tools | agents, chat, reasoning, structured_outputs, tools, vision |
Llama 4 Scout 17B 16E Instruct Capabilities
Qwen3.8 Max Capabilities
Related Comparisons
All image comparisons →| A | Pair | B | Context |
|---|---|---|---|
| vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text | |
Claude Fable 5.1Anthropic | vs | cross-developer peersimage, text | |
 Gemini 3.1 ProGoogle DeepMind | vs | cross-developer peerstext | |
 DeepSeek-V4.1-FlashDeepSeek | vs | cross-developer peersimage, text | |
| vs | Grok 4.6xAI | cross-developer peersimage, text | |
| vs |  Kimi-K3Moonshot AI | cross-developer peersimage, text | |
 MiniMax-M3MiniMax | vs | cross-developer peersimage, text | |
| vs |  GLM-5.3Z.ai | cross-developer peerstext | |
| vs |  Hy4 previewTencent | cross-developer peerstext | |
Seed 2.1 ProByteDance Seed | vs | cross-developer peersimage, text | |
| vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text | |
| vs | family variantsimage, text |
Primary Evidence
Sources and Freshness
Questions
Llama 4 Scout 17B 16E Instruct vs Qwen3.8 Max FAQs
Is Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E Instruct and Qwen3.8 Max, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max?+
Llama 4 Scout 17B 16E Instruct is $0.10 and Qwen3.8 Max is $1.65 per million tokens, so Llama 4 Scout 17B 16E Instruct is cheaper on this metric. Llama 4 Scout 17B 16E Instruct is $0.30 and Qwen3.8 Max is $4.951 per million tokens, so Llama 4 Scout 17B 16E Instruct is cheaper on this metric.
Which has a larger context window, Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max?+
Llama 4 Scout 17B 16E Instruct has the larger sourced context window. Llama 4 Scout 17B 16E Instruct supports 10,000K and Qwen3.8 Max supports 1,000K.
Which performs better in benchmarks, Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max be self-hosted?+
Llama 4 Scout 17B 16E Instruct is the only model in this pair currently marked as self-hostable. Llama 4 Scout 17B 16E Instruct is open weight; Qwen3.8 Max is not marked open weight.
Can Llama 4 Scout 17B 16E Instruct and Qwen3.8 Max understand images?+
Llama 4 Scout 17B 16E Instruct is documented with image input; Qwen3.8 Max is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max?+
Neither has a larger sourced maximum output. Llama 4 Scout 17B 16E Instruct is — and Qwen3.8 Max is 131K.
Do Llama 4 Scout 17B 16E Instruct and Qwen3.8 Max support reasoning and tool use?+
Llama 4 Scout 17B 16E Instruct: tool calling and image input. Qwen3.8 Max: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max?+
Llama 4 Scout 17B 16E Instruct has 4 sourced provider routes; Qwen3.8 Max has 4, a tie.
Which offers better value, Llama 4 Scout 17B 16E Instruct or Qwen3.8 Max?+
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.