Head-to-head
Llama 4 (Scout / Maverick) vs Claude Opus 4.7: which AI model wins in 2026?
Llama 4 (Scout / Maverick) ($0.60/1M out (Maverick, hosted)) and Claude Opus 4.7 ($25/1M out) are two of the most-used AI models in 2026. Across 3 community votes, Claude Opus 4.7 leads with 57% approval.
Quick verdict
On Reasoning, pick Claude Opus 4.7: the arena rates it 4.5/5 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 4.7.
Line-by-line comparison
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 4.7
- 87.6% SWE-bench Verified (up from 80.8% on Opus 4.6) and 64.3% SWE-bench Pro at launch, ahead of GPT-5.4 (57.7%) and Gemini 3.1 Pro (54.2%)
- 1M-token context window and 128K max output at flat $5/$25 pricing with no long-context premium (300K output via Batch API beta)
- First Claude with high-resolution vision: accepts images up to 2576px on the long edge with pixel-accurate coordinates, ~3x prior detail
- Standout code review: finds more real bugs with stronger cross-file reasoning than rivals in independent tests, and 21% fewer document-reasoning errors than Opus 4.6
- Fine cost control via new xhigh effort level and Task Budgets (beta): low-effort 4.7 roughly matches medium-effort 4.6 output quality
- Recent knowledge: reliable cutoff of January 2026, the freshest of any Claude model at release
- New tokenizer inflates token counts roughly 30% for the same text versus pre-4.7 models (per Anthropic's own docs), raising effective per-request cost despite the unchanged sticker price
- Very verbose in agentic use: one benchmark found GPT-5.5 used 72% fewer output tokens on equivalent coding tasks, and reviewers call its narration over-communicative
- Breaking API changes bite migrators: temperature/top_p/top_k and thinking budget_tokens now return 400 errors, and thinking text is hidden by default
- Moderate latency with minutes-long turns at high effort; fast mode is a premium research preview already deprecated on 4.7
- Superseded by Opus 4.8 at the same $5/$25 within ~3 months, and real-time cybersecurity safeguards can false-positive on legitimate security work
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
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 4.7
Choose Opus 4.7 only if you are already pinned to it for reproducibility: Opus 4.8 costs the same $5/$25, keeps an identical API surface, and outperforms it, making it the better default for new projects. It remains a very strong pick for agentic coding, code review and 1M-context document work, and is a clear upgrade over Opus 4.6. Teams migrating from 4.6 should budget for breaking API changes and a tokenizer that yields roughly 30% more tokens per prompt. Cost-sensitive users should look at Sonnet 5, which delivers near-Opus quality at $3/$15 (intro $2/$10 through August 31, 2026).
What the crowd says
On Llama 4 (Scout / Maverick)
No verdicts yet. Be the first to speak.
On Claude Opus 4.7
“Watch your invoices. New tokenizer counts ~30% more tokens for the same text, and it narrates every tiny step. Sticker price unchanged, effective cost definitely not.”
“Came from 4.6 and stopped chunking repos entirely. 1M context, 128K output, flat $5/$25 with no long-context premium. That pricing decision alone won me over.”
“87.6 SWE-bench Verified is not just marketing, it closes tickets GPT-5.4 fumbles. And the hi-res vision with pixel-accurate coords finally makes screenshot debugging useful.”
Keep comparing
Frequently asked questions
Is Llama 4 (Scout / Maverick) better than Claude Opus 4.7?
The crowd currently sides with Claude Opus 4.7: 57% recommend it, versus 50% for Llama 4 (Scout / Maverick) (3 votes). On Reasoning, Claude Opus 4.7 rates higher (4.5/5 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 4.7?
Llama 4 (Scout / Maverick) is cheaper: it starts at $0.60/1M out (Maverick, hosted), while Claude Opus 4.7 starts at $25/1M out.
How much do Llama 4 (Scout / Maverick) and Claude Opus 4.7 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 4.7: $5/1M in per 1M input tokens, $25/1M out per 1M output tokens.