Llama 4 Scout 17B 16E Instruct vs Kimi K2 Instruct
At a Glance
| Compare |  Kimi K2 InstructMoonshot AI | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Deepinfra ↗ · Sep 23, 2026 | $0.57Openrouter ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $0.30Deepinfra ↗ · Sep 23, 2026 | $2.30Openrouter ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 10,000K | 131K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 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 | Kimi-K2-Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboardv4-ede5081a24bc · overall_accuracy · leader | 28.1348% of row best · percent · Llama-4-Scout-17B-16E-Instruct (FC) | 59.06100% of row best · percent · Moonshotai-Kimi-K2-Instruct (FC) |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 benchmark winNo 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 | Kimi-K2-Instruct |
|---|---|---|
| Developer | Meta | Moonshot AI |
| Family | Llama 4 Scout 17b 16e Instruct | Kimi K2 Instruct |
| Model | Llama-4-Scout-17B-16E-Instruct | Kimi-K2-Instruct |
| Version | Llama-4-Scout-17B-16E-Instruct | Kimi-K2-Instruct |
| Lifecycle | active | active |
| Released | 2025-04-05 | 2025-07-11 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 10,000K | 131K |
| Total parameters | 108.6B | 1T |
| Active parameters | 17B | 32B |
| License | other | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, tools | chat, generation, tools |
Llama 4 Scout 17B 16E Instruct Capabilities
Kimi K2 Instruct Capabilities
Related Comparisons
All text 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 |  Qwen3.8-MaxQwen | 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 |
Primary Evidence
Sources and Freshness
Questions
Llama 4 Scout 17B 16E Instruct vs Kimi K2 Instruct FAQs
Is Llama 4 Scout 17B 16E Instruct or Kimi K2 Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E Instruct and Kimi K2 Instruct, 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 Kimi K2 Instruct?+
Llama 4 Scout 17B 16E Instruct is $0.10 and Kimi K2 Instruct is $0.57 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 Kimi K2 Instruct is $2.30 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 Kimi K2 Instruct?+
Llama 4 Scout 17B 16E Instruct has the larger sourced context window. Llama 4 Scout 17B 16E Instruct supports 10,000K and Kimi K2 Instruct supports 131K.
Which performs better in benchmarks, Llama 4 Scout 17B 16E Instruct or Kimi K2 Instruct?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Llama 4 Scout 17B 16E Instruct or Kimi K2 Instruct be self-hosted?+
Both models have the same recorded self-hosting status: supported. Llama 4 Scout 17B 16E Instruct is open weight; Kimi K2 Instruct is open weight.
Can Llama 4 Scout 17B 16E Instruct and Kimi K2 Instruct understand images?+
Llama 4 Scout 17B 16E Instruct is documented with image input; Kimi K2 Instruct is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 4 Scout 17B 16E Instruct or Kimi K2 Instruct?+
Neither has a larger sourced maximum output. Llama 4 Scout 17B 16E Instruct is — and Kimi K2 Instruct is —.
Do Llama 4 Scout 17B 16E Instruct and Kimi K2 Instruct support reasoning and tool use?+
Llama 4 Scout 17B 16E Instruct: tool calling and image input. Kimi K2 Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 4 Scout 17B 16E Instruct or Kimi K2 Instruct?+
Llama 4 Scout 17B 16E Instruct has 4 sourced provider routes; Kimi K2 Instruct has 2, so Llama 4 Scout 17B 16E Instruct has broader tracked availability.
Which offers better value, Llama 4 Scout 17B 16E Instruct or Kimi K2 Instruct?+
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.