Claude Sonnet 5 vs Llama 4 Maverick
Claude Sonnet 5 and Llama 4 Maverick sit at opposite ends of the price-performance curve. Sonnet 5 is Anthropic's current Sonnet-class flagship with adaptive reasoning effort levels; Maverick is Meta's MoE model (17B active params, 128 experts) optimized for throughput and cost. Both are available on OpenKey with one API key and a flat 3% fee on provider list pricing — the comparison below is about which one fits your workload, not which is 'better' in the abstract.
Spec vs spec
| Spec | Claude Sonnet 5 | Llama 4 Maverick |
|---|---|---|
| Context window | 1M | 1.0M |
| Max output | 128K | 16K |
| Input modalities | text, image, file | text, image |
| Output modalities | text | text |
| Knowledge cutoff | — | Aug 31, 2024 |
| Released | Jun 30, 2026 | Apr 5, 2025 |
| Reasoning | optional | — |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
anthropic/claude-sonnet-5
Input · 1M tokens
$2.00 + 3%$2.06
Output · 1M tokens
$10.00 + 3%$10.30
Cache read · 1M tokens
$0.200 + 3%$0.206
Cache write · 1M tokens
$2.50 + 3%$2.58
FEE — FLAT, EVERY MODEL3%
meta-llama/llama-4-maverick
Input · 1M tokens
$0.150 + 3%$0.154
Output · 1M tokens
$0.600 + 3%$0.618
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
anthropic/claude-sonnet-5
$41.20
$40.00 provider + 3%
meta-llama/llama-4-maverickCheaper
$2.78
$2.70 provider + 3%
Pricing math on a real workload
For 10M input tokens + 2M output tokens: Claude Sonnet 5 costs $40.00, Llama 4 Maverick costs $2.70. That's roughly a 15x gap on this exact mix, driven by an input price ratio of 13.33x ($2.00/M vs $0.15/M provider price). On OpenKey, Sonnet 5 runs at $2.06/M input and $10.30/M output (provider price x 1.03); Maverick runs at $0.1545/M input and $0.618/M output. Sonnet 5 also bills cache reads at $0.20/M and cache writes at $2.50/M — Maverick has no cache pricing listed, so repeated-context workloads don't get a discount lever there. If your workload is prompt-heavy and repeated, that cache pricing on Sonnet 5 can close some of the gap; Maverick's flat low rate has no such nuance to plan around.
Coding and agentic performance
The artificial_analysis benchmarks show a wide separation: Sonnet 5 scores 71.5 on coding and 46.7 on agentic tasks, versus Maverick's 16.3 and 1.3. That agentic gap in particular — 46.7 vs 1.3 — matters if you're building anything with tool calls, multi-step planning, or autonomous loops. Maverick does have Design Arena rankings across six categories (3d, codecategories, dataviz, gamedev, uicomponent, website), with elo scores between 903 and 976 and ranks in the 91-105 range out of the field it was measured against — respectable for its price tier, but not benchmark data that exists for Sonnet 5 in this dataset, so a direct elo comparison isn't possible.
Context and output limits
Context windows are close: Sonnet 5 at 1,000,000 tokens, Maverick at 1,048,576 tokens — a context ratio of 0.95, effectively a wash for most use cases. The real difference is max output: Sonnet 5 can generate up to 128,000 tokens in a single completion, Maverick caps at 16,384. If your task involves generating long documents, large codebases, or extended agent transcripts in one pass, Sonnet 5's output ceiling is 8x higher and will matter well before context length does.
Modality and tooling differences
Sonnet 5 accepts text, image, and file input; Maverick accepts text and image only — no native file input. Sonnet 5 also exposes reasoning controls (`reasoning`, `include_reasoning`, `verbosity`) with five effort levels (low, medium, high, xhigh, max) and a medium default, useful for trading off latency against depth on a per-request basis. Maverick has no reasoning parameter at all, but supports a longer list of sampling controls — `top_k`, `min_p`, `repetition_penalty`, `logit_bias`, `logprobs`, `seed` — giving you finer-grained control over generation behavior if you're tuning output diversity or need deterministic runs.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| Autonomous coding agents / tool-calling pipelines | Claude Sonnet 5 | Agentic index of 46.7 vs Maverick's 1.3 |
| High-volume batch classification or summarization | Llama 4 Maverick | $2.70 vs $40.00 on a 10M-in/2M-out workload |
| Long single-pass generation (large docs, big diffs) | Claude Sonnet 5 | 128,000 max output tokens vs 16,384 |
| File-based document analysis (PDFs, attachments) | Claude Sonnet 5 | Only Sonnet 5 supports file input modality |
| Cost-sensitive prototyping at scale | Llama 4 Maverick | Input price of $0.1545/M on OpenKey vs $2.06/M |
| Fine-grained sampling control (seed, top_k, logit_bias) | Llama 4 Maverick | Exposes top_k, min_p, repetition_penalty, seed, logprobs — Sonnet 5 doesn't |
Questions
- How much more expensive is Claude Sonnet 5 than Llama 4 Maverick?
- On a 10M input + 2M output token workload, Sonnet 5 costs $40.00 versus Maverick's $2.70 — about 15x more. The input price ratio alone is 13.33x ($2.00/M vs $0.15/M provider price before the OpenKey 3% fee).
- Which model has the longer context window?
- They're nearly tied. Maverick supports 1,048,576 tokens of context and Sonnet 5 supports 1,000,000 — a context ratio of 0.95. The bigger gap is max output: Sonnet 5 allows 128,000 tokens per completion versus Maverick's 16,384.
- Does Llama 4 Maverick support reasoning effort levels like Sonnet 5?
- No. Sonnet 5 exposes a `reasoning` parameter with five selectable effort levels (low, medium, high, xhigh, max, default medium). Maverick has no reasoning field in its supported parameters at all — it's a standard MoE model without adaptive thinking controls.
- Can I use both models through the same API key?
- Yes. Both Claude Sonnet 5 and Llama 4 Maverick are available on OpenKey, which routes to 329 models from 52 labs through one key, billed at provider list price plus a flat 3% fee — $2.06/M input for Sonnet 5 and $0.1545/M input for Maverick.