LLM Reference

Claude Opus 4.8 vs Claude Sonnet 4.6

Both models are Anthropic's current production family on the Anthropic API, AWS Bedrock, and Google Vertex AI with a shared 1M-token context window. The choice is a cost-vs-capability trade: Claude Sonnet 4.6 costs $3/M input and $15/M output with a 64K max output; Claude Opus 4.8 costs $5/M input and $25/M output with a 128K max output, a stronger benchmark profile across SWE-bench, GPQA, and LiveCodeBench, and a Fast Mode research preview at $10/M input and $50/M output for latency-sensitive workloads.

Pick Claude Opus 4.8 when agentic coding quality, long-horizon reasoning, or computer-use accuracy is the primary constraint: it leads SWE-bench Verified 88.6% vs 79.6%, SWE-bench Pro 69.2%, GPQA Diamond 93.6% vs 89.9%, LiveCodeBench 88.8% vs 80%, and has a 128K vs 64K max output ceiling. Pick Claude Sonnet 4.6 when cost or throughput is the bottleneck: it is 40% cheaper on input and output tokens while sharing the same 1M context window, provider availability, prompt caching, Batch API support, and multimodal capabilities. Default to Sonnet 4.6 for high-volume pipelines, summarization, and tool-use agents where benchmark gaps do not visibly affect quality; upgrade to Opus 4.8 for SWE-bench-class coding agents, multi-step computer-use tasks, and hard-science reasoning where the ~9-point benchmark gap translates to real outcome differences.

Decision scorecard

Local evidence first
SignalClaude Opus 4.8Claude Sonnet 4.6
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsreasoning-heavy apps, multimodal apps, and tool-calling agents
Decision fitCoding, RAG, and AgentsCoding, RAG, and Agents
Context window1m1m
Cheapest output$25/1M tokens$15/1M tokens
Provider routes6 tracked6 tracked
Shared benchmarksSWE-bench Verified leader5 shared

Decision tradeoffs

Choose Claude Opus 4.8 when...
  • Claude Opus 4.8 holds a shared-benchmark lead on SWE-bench Verified, ahead by 9 points.
  • Local decision data tags Claude Opus 4.8 for Coding, RAG, and Agents.
Choose Claude Sonnet 4.6 when...
  • Claude Sonnet 4.6 has the lower cheapest tracked output price at $15/1M tokens.
  • Local decision data tags Claude Sonnet 4.6 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.

Lower estimate Claude Sonnet 4.6

Claude Opus 4.8

$10,250

Cheapest tracked route/tier: Anthropic

Claude Sonnet 4.6

$6,150

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $4,100. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Claude Opus 4.8 -> Claude Sonnet 4.6
  • Provider overlap exists on OpenRouter, Anthropic, and AWS Bedrock; start route-level A/B tests there.
  • Claude Sonnet 4.6 is $10/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Claude Sonnet 4.6 -> Claude Opus 4.8
  • Provider overlap exists on Anthropic, AWS Bedrock, and GCP Vertex AI; start route-level A/B tests there.
  • Claude Opus 4.8 is $10/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.

Specs

Specification
Released2026-05-282026-02-17
Context window1m1m
Parameters
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryProprietary
OpennessProprietaryProprietary
WeightsNot releasedNot released
CodeNot releasedUnknown
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff2026-012025-08

Pricing and availability

Pricing attributeClaude Opus 4.8Claude Sonnet 4.6
Input price$5/1M tokens$3/1M tokens
Output price$25/1M tokens$15/1M tokens
Providers

Capabilities

CapabilityClaude Opus 4.8Claude Sonnet 4.6
VisionYesYes
MultimodalYesYes
ReasoningYesYes
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionYesYes
IDE integrationNoNo
Computer useYesYes
Parallel agentsYesYes

Benchmarks

BenchmarkClaude Opus 4.8Claude Sonnet 4.6
SWE-bench Verified88.679.6
Google-Proof Q&A93.689.9
LiveCodeBench88.880.0
MCP-Atlas82.261.3
CursorBench63.849.0

Deep dive

Pricing is the first filter. Claude Sonnet 4.6 is $3/M input and $15/M output via the Anthropic API, with batch at $1.5/M input and $7.5/M output, cache reads at $0.30/M, and cache write at $3.75/M (5 min) and $6/M (1 hr). Claude Opus 4.8 is $5/M input and $25/M output, batch at $2.5/M input and $12.5/M output, cache reads at $0.50/M, and cache write at $6.25/M (5 min) and $10/M (1 hr). Opus 4.8 also has a Fast Mode research preview at $10/M input and $50/M output that is not available in Batch API. At 10M monthly input tokens, the difference is $20,000/year — relevant for high-volume API consumers.

The capability gap is real but task-dependent. On agentic coding, Opus 4.8 leads SWE-bench Verified by 9 points (88.6% vs 79.6%) and SWE-bench Pro by a published 69.2% with no comparable Sonnet 4.6 row. GPQA Diamond widens to a 3.7-point gap (93.6% vs 89.9%), and LiveCodeBench sits at 88.8% vs 80%. These are Anthropic launch benchmarks and secondary sources — treat them as directional signals, not certified head-to-head evaluations. The gap is largest in coding, reasoning, and computer-use tasks; for summarization, translation, RAG, and routine tool-calling, the gap frequently does not materialize in end-to-end quality.

Both models share the same infrastructure footprint. Each has a 1M-token context window, vision, function calling, structured outputs, code execution, computer use, parallel agents, prompt caching, and Batch API availability on Anthropic API, AWS Bedrock, and Google Vertex AI. The output ceiling differs: Opus 4.8 supports 128K max output tokens vs Sonnet 4.6's 64K, which matters for tasks that produce long documents, large diffs, or extended multi-step plans in a single call.

The upgrade decision reduces to output quality per dollar. For a team running 5M input tokens per month: Sonnet 4.6 costs $15K/year in input, Opus 4.8 costs $25K/year — a $10K difference. If upgrading closes even one meaningful failure mode per month (a bad code patch, a missed edge case in a reasoning chain), the cost is often justified. If the workload is throughput-bound and quality differences are not user-visible, Sonnet 4.6 is the better default.

FAQ

How much more expensive is Claude Opus 4.8 than Claude Sonnet 4.6?

Claude Opus 4.8 costs $5/M input and $25/M output via the Anthropic API. Claude Sonnet 4.6 costs $3/M input and $15/M output. Opus 4.8 is approximately 67% more expensive on both input and output tokens. Both models offer Batch API pricing at half the standard rate.

Which is better for coding agents, Claude Opus 4.8 or Sonnet 4.6?

Claude Opus 4.8 leads on the benchmarks most relevant to coding agents: SWE-bench Verified 88.6% vs 79.6%, LiveCodeBench 88.8% vs 80%, and a published SWE-bench Pro score of 69.2% with no directly comparable Sonnet 4.6 row. For agentic coding workflows where task-completion rate matters, Opus 4.8 is the stronger default. Sonnet 4.6 is a reasonable starting point for code review, code generation, and simpler coding tasks where the benchmark gap does not translate to measurable outcome differences.

Do both models support the same context window?

Yes. Both Claude Opus 4.8 and Claude Sonnet 4.6 support a 1M-token context window on the Anthropic API, AWS Bedrock, and Google Vertex AI. The maximum output token limit differs: Opus 4.8 supports 128K max output tokens; Sonnet 4.6 supports 64K.

Which model should I use for high-volume API workloads?

Claude Sonnet 4.6 is the standard choice for high-volume workloads where cost is a constraint and benchmark-level quality differences are not visibly impactful. It has the same provider availability, prompt caching, and Batch API access as Opus 4.8 at 40% lower token prices.

What is Claude Opus 4.8 Fast Mode?

Fast Mode is a research preview available for Claude Opus 4.8 that reduces latency at a higher token price: $10/M input and $50/M output. It is not available via the Batch API. Sonnet 4.6 does not have a Fast Mode tier; its standard pricing is already lower than Opus 4.8 standard.

Continue comparing

Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.