Head-to-head
Llama 4 (Scout / Maverick) vs Claude Opus 4.5: which AI model wins in 2026?
Llama 4 (Scout / Maverick) ($0.60/1M out (Maverick, hosted)) and Claude Opus 4.5 ($25/1M out) are two of the most-used AI models in 2026. Compare them line by line below, then cast your verdict.
Quick verdict
On Reasoning, pick Claude Opus 4.5: the arena rates it 3.5/5 against 2.5/5 for Llama 4 (Scout / Maverick). On budget, Llama 4 (Scout / Maverick) wins: it starts at $0.60/1M out (Maverick, hosted) versus $25/1M out for Claude Opus 4.5.
Line-by-line comparison
From
$0.60/1M out (Maverick, hosted)No first-party paid Meta API; typical third-party hosted rates shown for Maverick (Scout from ~$0.10/$0.30 per 1M on DeepInfra, $0.11/$0.34 on Groq). Hosted Scout context is capped well below the 10M nominal spec (e.g. ~320K on DeepInfra).
$25/1M outOfficial Anthropic API list price for claude-opus-4-5 (single tier, no long-context premium; 200K context, 64K max output); same $5/$25 rate as its Opus 4.6-4.8 successors; 50% batch discount and prompt caching apply. Verified against platform.claude.com models overview 2026-07.
Provider
Meta
Anthropic
Context window
10M tokens (Scout) / 1M (Maverick)
200K tokens
Input price
$0.15/1M in (Maverick, hosted)
$5/1M in
Output price
$0.60/1M out (Maverick, hosted)
$25/1M out
Modalities
text, vision (image input)
text, vision
Open weights
Yes
No
Crowd score
50%(0)
50%(0)
Arena ratings (1-5)
Reasoning
2.5
3.5
Coding
2.0
3.5
Writing
2.5
3.5
Speed
4.5
2.5
Value
3.5
2.5
Strengths and weaknesses
Llama 4 (Scout / Maverick)
- MoE efficiency: only 17B active parameters per token (Scout 109B/16 experts, Maverick 400B/128 experts), giving near GPT-4o-class chat at a fraction of the compute
- Very cheap hosted inference: Maverick from about $0.15/1M in and $0.60/1M out; Scout from about $0.10/$0.30 on DeepInfra or $0.11/$0.34 on Groq
- Native early-fusion multimodality (text plus images, tested up to 8 images) in an open-weight model
- Largest nominal context of any open-weight model at release: 10M tokens on Scout, 1M on Maverick
- Scout fits on a single H100 GPU with Int4 quantization; pretrained on 200 languages
- High throughput: 17B active params reach 500+ tokens/s on fast providers (Groq lists Scout at 594 TPS)
- Benchmark trust damaged: Meta submitted an unreleased chat-optimized Maverick variant to LMArena (ELO 1417), which devs called misleading since public weights score lower
- Long-context claims collapse in practice: Scout scored ~15.6% at 128K on Fiction.LiveBench vs 90.6% for Gemini 2.5 Pro, and hosted providers cap Scout far below 10M (e.g. ~320K on DeepInfra)
- Coding widely panned on r/LocalLlama and HN, losing to the similarly-priced DeepSeek V3 on real dev tasks
- Not OSI open source: license excludes EU-domiciled companies, requires a special license above 700M MAU, and mandates Llama branding
- 109B/400B total params are too big for consumer GPUs, and the lineage stalled: no reasoning variant shipped and Behemoth was never released
Claude Opus 4.5
- First model past 80% on SWE-bench Verified (80.9% at launch), beating Gemini 3 Pro and GPT-5.1 on real-world coding
- 66% price cut vs Opus 4.1 ($5/$25 vs $15/$75 per 1M tokens) made Opus-tier viable for production workloads
- 48-76% fewer output tokens than Sonnet 4.5 at matched or better quality, compounding the price cut
- Effort parameter (introduced with this model) lets devs trade reasoning depth for cost and latency per call
- Strong hands-on reports: one-shot complex refactors, caught race conditions other models missed, converged in ~4 agentic iterations vs ~10 for rivals
- +29% on Vending-Bench vs Sonnet 4.5, with fewer dead-ends on long-horizon autonomous tasks
- 200K context window only (64K max output), far behind the 1M of Gemini 3 Pro and later Claude models; users reported selective attention above ~70% context fill
- Gated to $100-200/month Max tiers in Claude apps at launch; Pro subscribers were locked out and heavy users still hit limits (HN called it 'penny-wise and pound-foolish')
- Moderate latency; extended thinking adds cost and delay on simple tasks
- Superseded since early 2026: Opus 4.6/4.7/4.8 cost the same $5/$25 with 1M context and higher benchmarks, leaving 4.5 no price advantage
- Legacy API surface: manual budget_tokens extended thinking rather than the adaptive thinking of newer Claude models
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
Llama 4 (Scout / Maverick)$0.60/1M out (Maverick, hosted)
50%crowd score · 0
Claude Opus 4.5$25/1M out
50%crowd score · 0
The arena’s verdict on Llama 4 (Scout / Maverick)
Pick Llama 4 if you need a cheap, fast, self-hostable multimodal model for high-volume chat, extraction, or multilingual workloads outside the EU; Maverick lands near GPT-4o quality at roughly a tenth of the price. Avoid it for coding, hard reasoning, or genuine million-token retrieval, where DeepSeek, Qwen 3, and Gemini clearly outperform it. Versus Llama 3.3 70B it adds native vision and a longer window, but many developers found the older dense model or Qwen more reliable for pure text quality, and the 10M context is mostly a paper number.
The arena’s verdict on Claude Opus 4.5
Pick Claude Opus 4.5 only if you have a workload already tuned and pinned to this snapshot (claude-opus-4-5-20251101) and need stability. It was a landmark release, the first past 80% on SWE-bench Verified and a 66% price cut over Opus 4.1, but Anthropic now sells Opus 4.6 through 4.8 at the identical $5/$25 rate with a 1M context window and better scores. Anyone starting a new project should choose Opus 4.8 instead, and cost-sensitive users get near-Opus coding from Sonnet 5 at $3/$15 (intro $2/$10 through Aug 2026). Avoid it entirely if your prompts approach the 200K context ceiling.
Keep comparing
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Frequently asked questions
Is Llama 4 (Scout / Maverick) better than Claude Opus 4.5?
On Reasoning, Claude Opus 4.5 rates higher (3.5/5 vs 2.5/5). The right pick depends on your use case. The line-by-line comparison on this page breaks down pricing, key specs and arena ratings.
Which is cheaper, Llama 4 (Scout / Maverick) or Claude Opus 4.5?
Llama 4 (Scout / Maverick) is cheaper: it starts at $0.60/1M out (Maverick, hosted), while Claude Opus 4.5 starts at $25/1M out.
How much do Llama 4 (Scout / Maverick) and Claude Opus 4.5 cost per 1M tokens?
Llama 4 (Scout / Maverick): $0.15/1M in (Maverick, hosted) per 1M input tokens, $0.60/1M out (Maverick, hosted) per 1M output tokens. Claude Opus 4.5: $5/1M in per 1M input tokens, $25/1M out per 1M output tokens.