Claude Sonnet 4.6 vs Llama 4 Maverick 17B Instruct FP8
Claude Sonnet 4.6 (2026) and Llama 4 Maverick 17B Instruct FP8 (2025) are frontier reasoning models from Anthropic and AI at Meta. Claude Sonnet 4.6 ships a 1m-token context window, while Llama 4 Maverick 17B Instruct FP8 ships a 1m-token context window. On MMLU PRO, Claude Sonnet 4.6 leads by 6.8 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 4 Maverick 17B Instruct FP8 is ~1900% cheaper at $0.15/1M; pay for Claude Sonnet 4.6 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Claude Sonnet 4.6 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps, long-context analysis, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 1m |
| Cheapest output | $15/1M tokens | $0.60/1M tokens |
| Provider routes | 6 tracked | 10 tracked |
| Shared benchmarks | MMLU PRO leader | 8 shared |
Decision tradeoffs
- Claude Sonnet 4.6 holds a shared-benchmark lead on MMLU PRO, ahead by 6.8 points.
- Claude Sonnet 4.6 uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags Claude Sonnet 4.6 for Coding, RAG, and Agents.
- Llama 4 Maverick 17B Instruct FP8 has the lower cheapest tracked output price at $0.60/1M tokens.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Claude Sonnet 4.6
$6,150
Cheapest tracked route/tier: OpenRouter
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $5,880. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Microsoft Foundry, OpenRouter, and GCP Vertex AI; start route-level A/B tests there.
- Llama 4 Maverick 17B Instruct FP8 is $14.40/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- Provider overlap exists on OpenRouter, AWS Bedrock, and GCP Vertex AI; start route-level A/B tests there.
- Claude Sonnet 4.6 is $14.40/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Claude Sonnet 4.6 adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-17 | 2025-04-05 |
| Context window | 1m | 1m |
| Parameters | — | 400B (17B active) |
| Architecture | Decoder Only | Mixture of Experts |
| License | Proprietary | Llama 4 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use: conditional | Commercial use: conditional |
| Knowledge cutoff | 2025-08 | 2024-08 |
Pricing and availability
| Pricing attribute | Claude Sonnet 4.6 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Input price | $3/1M tokens | $0.15/1M tokens |
| Output price | $15/1M tokens | $0.60/1M tokens |
| Providers |
Capabilities
| Capability | Claude Sonnet 4.6 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | Yes | No |
| Parallel agents | Yes | No |
Benchmarks
| Benchmark | Claude Sonnet 4.6 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| MMLU PRO | 87.3 | 80.5 |
| Google-Proof Q&A | 89.9 | 67.1 |
| LiveCodeBench | 80.0 | 43.4 |
| Massive Multi-discipline Multimodal Understanding | 83.6 | 73.4 |
| HumanEval | 98.0 | 77.4 |
| Chatbot Arena | 1459.0 | 1365.0 |
| τ-bench | 87.5 | 68.5 |
| MMMU Pro | 75.6 | 59.6 |
Deep dive
On shared benchmark coverage, MMLU PRO has Claude Sonnet 4.6 at 87.3 and Llama 4 Maverick 17B Instruct FP8 at 80.5, with Claude Sonnet 4.6 ahead by 6.8 points; Google-Proof Q&A has Claude Sonnet 4.6 at 89.9 and Llama 4 Maverick 17B Instruct FP8 at 67.1, with Claude Sonnet 4.6 ahead by 22.8 points; LiveCodeBench has Claude Sonnet 4.6 at 80 and Llama 4 Maverick 17B Instruct FP8 at 43.4, with Claude Sonnet 4.6 ahead by 36.6 points. The largest visible gap is 36.6 points on LiveCodeBench, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on reasoning mode: Claude Sonnet 4.6, function calling: Claude Sonnet 4.6, tool use: Claude Sonnet 4.6, and code execution: Claude Sonnet 4.6. Both models share vision, multimodal input, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Claude Sonnet 4.6 lists $3/1M input and $15/1M output tokens on the cheapest tracked provider, while Llama 4 Maverick 17B Instruct FP8 lists $0.15/1M input and $0.60/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Maverick 17B Instruct FP8 lower by about $6.31 per million blended tokens. Availability is 6 providers versus 10, so concentration risk also matters.
Choose Claude Sonnet 4.6 when coding workflow support are central to the workload. Choose Llama 4 Maverick 17B Instruct FP8 when vision-heavy evaluation, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Claude Sonnet 4.6 or Llama 4 Maverick 17B Instruct FP8?
Claude Sonnet 4.6 supports 1m tokens, while Llama 4 Maverick 17B Instruct FP8 supports 1m tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Claude Sonnet 4.6 or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 is cheaper on tracked token pricing. Claude Sonnet 4.6 costs $3/1M input and $15/1M output tokens. Llama 4 Maverick 17B Instruct FP8 costs $0.15/1M input and $0.60/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Claude Sonnet 4.6 or Llama 4 Maverick 17B Instruct FP8 open source?
Claude Sonnet 4.6 is listed under Proprietary. Llama 4 Maverick 17B Instruct FP8 is listed under Llama 4 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Claude Sonnet 4.6 or Llama 4 Maverick 17B Instruct FP8?
Both Claude Sonnet 4.6 and Llama 4 Maverick 17B Instruct FP8 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Claude Sonnet 4.6 or Llama 4 Maverick 17B Instruct FP8?
Both Claude Sonnet 4.6 and Llama 4 Maverick 17B Instruct FP8 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Claude Sonnet 4.6 and Llama 4 Maverick 17B Instruct FP8?
Claude Sonnet 4.6 is available on OpenRouter, Anthropic, AWS Bedrock, GCP Vertex AI, and Microsoft Foundry. Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.