Llama 4 Scout 17B 16E Instruct vs GLM 5
At a Glance
| Compare |  GLM 5Z.ai | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Deepinfra ↗ · Sep 23, 2026 | $0.60Deepinfra ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.30Deepinfra ↗ · Sep 23, 2026 | $1.92Openrouter ↗ · Aug 28, 2026 |
| Context windowMaximum documented tokens | 10,000K | 203K |
| 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 | GLM-5 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,279.2988% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1274.57681953, 1284.00026285]; votes 29740; rank 259 | 1,446.27100% of row best · rating · glm-5; 95% CI [1441.95071870, 1450.59229773]; votes 27605; rank 51 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 47.3257% of row best · points · Llama 4 Scout · 696 output tokens / case | 82.89100% of row best · points · GLM-5 · 15,496 output tokens / case |
| 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 | GLM-5 |
|---|---|---|
| Developer | Meta | Z.ai |
| Family | Llama 4 Scout 17b 16e Instruct | Glm 5 |
| Model | Llama-4-Scout-17B-16E-Instruct | GLM-5 |
| Version | Llama-4-Scout-17B-16E-Instruct | GLM-5 |
| Lifecycle | active | active |
| Released | 2025-04-05 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 10,000K | 203K |
| Total parameters | 108.6B | 753.9B |
| Active parameters | 17B | Unknown |
| License | other | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, tools |
Llama 4 Scout 17B 16E Instruct Capabilities
GLM 5 Capabilities
Related Comparisons
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|---|---|---|---|
| vs |  GPT-6 AstraOpenAI | cross-developer peersimage, text | |
Claude Fable 5.1Anthropic | vs | cross-developer peersimage, text | |
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 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 GLM 5 FAQs
Is Llama 4 Scout 17B 16E Instruct or GLM 5 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E Instruct and GLM 5, 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 GLM 5?+
Llama 4 Scout 17B 16E Instruct is $0.10 and GLM 5 is $0.60 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 GLM 5 is $1.92 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 GLM 5?+
Llama 4 Scout 17B 16E Instruct has the larger sourced context window. Llama 4 Scout 17B 16E Instruct supports 10,000K and GLM 5 supports 203K.
Which performs better in benchmarks, Llama 4 Scout 17B 16E Instruct or GLM 5?+
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 GLM 5 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Llama 4 Scout 17B 16E Instruct is open weight; GLM 5 is open weight.
Can Llama 4 Scout 17B 16E Instruct and GLM 5 understand images?+
Llama 4 Scout 17B 16E Instruct is documented with image input; GLM 5 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 GLM 5?+
Neither has a larger sourced maximum output. Llama 4 Scout 17B 16E Instruct is — and GLM 5 is —.
Do Llama 4 Scout 17B 16E Instruct and GLM 5 support reasoning and tool use?+
Llama 4 Scout 17B 16E Instruct: tool calling and image input. GLM 5: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 4 Scout 17B 16E Instruct or GLM 5?+
Llama 4 Scout 17B 16E Instruct has 4 sourced provider routes; GLM 5 has 4, a tie.
Which offers better value, Llama 4 Scout 17B 16E Instruct or GLM 5?+
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.