Claude Opus 5.5 vs DeepSeek R1
At a Glance
| Compare | Claude Opus 5.5Anthropic |  DeepSeek R1DeepSeek |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $4.00Anthropic ↗ · Sep 22, 2026 | $0.70Openrouter ↗ · Aug 28, 2026 |
| Output priceFrom · USD / 1M tokens | $20.00Anthropic ↗ · Sep 22, 2026 | $2.50Openrouter ↗ · Aug 28, 2026 |
| Context windowMaximum documented tokens | 1,000K | 164K |
| Model facts checked | Sep 22, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Claude Opus 5.5 | DeepSeek-R1 |
|---|---|---|
| Developer | Anthropic | DeepSeek |
| Family | Claude 5 5 | Deepseek R1 |
| Model | Claude Opus 5.5 | DeepSeek-R1 |
| Version | Claude Opus 5.5 | DeepSeek-R1 |
| Lifecycle | active | active |
| Released | 2026-09-22 | 2025-01-20 |
| Knowledge cutoff | 2026-06-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 164K |
| Total parameters | Unknown | 684.5B |
| Active parameters | Unknown | 37B |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning |
| Message Batches max output (beta) | 300000 tokens | Unknown |
| Default effort | medium | Unknown |
| Retirement commitment | Not sooner than September 22, 2027 | Unknown |
| Thinking | Adaptive (always on) | Unknown |
Claude Opus 5.5 Capabilities
DeepSeek R1 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Claude Opus 5.5 vs DeepSeek R1 FAQs
Is Claude Opus 5.5 or DeepSeek R1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 5.5 and DeepSeek R1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 5.5 or DeepSeek R1?+
Claude Opus 5.5 is $4.00 and DeepSeek R1 is $0.70 per million tokens, so DeepSeek R1 is cheaper on this metric. Claude Opus 5.5 is $20.00 and DeepSeek R1 is $2.50 per million tokens, so DeepSeek R1 is cheaper on this metric.
Which has a larger context window, Claude Opus 5.5 or DeepSeek R1?+
Claude Opus 5.5 has the larger sourced context window. Claude Opus 5.5 supports 1,000K and DeepSeek R1 supports 164K.
Which performs better in benchmarks, Claude Opus 5.5 or DeepSeek R1?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Opus 5.5 or DeepSeek R1 be self-hosted?+
DeepSeek R1 is the only model in this pair currently marked as self-hostable. Claude Opus 5.5 is not marked open weight; DeepSeek R1 is open weight.
Can Claude Opus 5.5 and DeepSeek R1 understand images?+
Claude Opus 5.5 is documented with image input; DeepSeek R1 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 5.5 or DeepSeek R1?+
Claude Opus 5.5 has the larger sourced maximum output: Claude Opus 5.5 supports 128K and DeepSeek R1 supports 33K output tokens.
Do Claude Opus 5.5 and DeepSeek R1 support reasoning and tool use?+
Claude Opus 5.5: reasoning, tool calling, and image input. DeepSeek R1: reasoning. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 5.5 or DeepSeek R1?+
Claude Opus 5.5 has 1 sourced provider route; DeepSeek R1 has 2, so DeepSeek R1 has broader tracked availability.
Which offers better value, Claude Opus 5.5 or DeepSeek R1?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.