Claude Opus 4.6 vs DeepSeek V4 Pro 0813
At a Glance
| Compare | Claude Opus 4.6Anthropic |  DeepSeek V4 Pro 0813DeepSeek |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #12 of 4676.2 score · 3/3 sources · complete | #20 of 4665.0 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | #33 of 44$0.241 per LiveBench case | #20 of 44$0.094 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | #19 of 3853.2 score · 3/3 sources · complete | #14 of 3857.4 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $5.00Anthropic ↗ · Sep 3, 2026 | $1.30Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $25.00Anthropic ↗ · Sep 3, 2026 | $2.60Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,000K | 1,049K |
| Model facts checked | Sep 3, 2026View model evidence → | Sep 3, 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
| Benchmark | Claude Opus 4.6 | DeepSeek-V4-Pro-0813 |
|---|---|---|
| ARC-AGI-1verified-v1-ba05d69f6453 · verified_score · leader | 94.00100% of row best · percent · Claude Opus 4.6 (120K, High) | 90.5096% of row best · percent · DeepSeek V4 Pro 0813 (Low) |
| ARC-AGI-2verified-v2-6c676fa3e9af · verified_score · leader | 69.17100% of row best · percent · Claude Opus 4.6 (120K, High) | 61.2589% of row best · percent · DeepSeek V4 Pro 0813 (Max) |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,497.54100% of row best · rating · claude-opus-4-6; 95% CI [1494.14263199, 1500.94441396]; votes 75878; rank 5 | 1,443.9596% of row best · rating · deepseek-v4-pro-high-20260813; 95% CI [1437.16050212, 1450.73220317]; votes 9008; rank 58 |
| LiveBench2026-06-25 · overall · leader | 78.6996% of row best · percent · claude-opus-4-6-thinking-auto-high-effort · 9,651 output tokens / case | 81.91100% of row best · percent · deepseek-v4-pro-0813 · 36,339 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 84.2199% of row best · points · Claude Opus 4.6 · 13,556 output tokens / case | 84.68100% of row best · points · DeepSeek V4 Pro 0813 (max) · 18,462 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 3 benchmark winsOverall lead | 1 benchmark win |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Opus 4.6 | DeepSeek-V4-Pro-0813 |
|---|---|---|
| Developer | Anthropic | DeepSeek |
| Family | Claude 4 | Deepseek V4 Pro |
| Model | Claude Opus 4.6 | DeepSeek-V4-Pro-0813 |
| Version | Claude Opus 4.6 | DeepSeek-V4-Pro-0813 |
| Lifecycle | active | active |
| Released | 2026-02-05 | 2026-08-13 |
| Knowledge cutoff | 2025-05-01 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 1,049K |
| Total parameters | Unknown | 1.6T |
| Active parameters | Unknown | 49B |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | agents, chat, coding, generation, reasoning, tools |
Claude Opus 4.6 Capabilities
DeepSeek V4 Pro 0813 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Claude Opus 4.6 vs DeepSeek V4 Pro 0813 FAQs
Is Claude Opus 4.6 or DeepSeek V4 Pro 0813 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.6 and DeepSeek V4 Pro 0813, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Opus 4.6 or DeepSeek V4 Pro 0813?+
Claude Opus 4.6 is $5.00 and DeepSeek V4 Pro 0813 is $1.30 per million tokens, so DeepSeek V4 Pro 0813 is cheaper on this metric. Claude Opus 4.6 is $25.00 and DeepSeek V4 Pro 0813 is $2.60 per million tokens, so DeepSeek V4 Pro 0813 is cheaper on this metric.
Which has a larger context window, Claude Opus 4.6 or DeepSeek V4 Pro 0813?+
DeepSeek V4 Pro 0813 has the larger sourced context window. Claude Opus 4.6 supports 1,000K and DeepSeek V4 Pro 0813 supports 1,049K.
Which performs better in benchmarks, Claude Opus 4.6 or DeepSeek V4 Pro 0813?+
Claude Opus 4.6 leads the current overall benchmark count. The result uses 4 protocol-matched benchmarks from 3 publishers; it is not a universal quality score.
Can Claude Opus 4.6 or DeepSeek V4 Pro 0813 be self-hosted?+
DeepSeek V4 Pro 0813 is the only model in this pair currently marked as self-hostable. Claude Opus 4.6 is not marked open weight; DeepSeek V4 Pro 0813 is open weight.
Can Claude Opus 4.6 and DeepSeek V4 Pro 0813 understand images?+
Claude Opus 4.6 is documented with image input; DeepSeek V4 Pro 0813 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Opus 4.6 or DeepSeek V4 Pro 0813?+
Neither has a larger sourced maximum output. Claude Opus 4.6 is 128K and DeepSeek V4 Pro 0813 is —.
Do Claude Opus 4.6 and DeepSeek V4 Pro 0813 support reasoning and tool use?+
Claude Opus 4.6: reasoning, tool calling, and image input. DeepSeek V4 Pro 0813: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Opus 4.6 or DeepSeek V4 Pro 0813?+
Claude Opus 4.6 has 1 sourced provider route; DeepSeek V4 Pro 0813 has 3, so DeepSeek V4 Pro 0813 has broader tracked availability.
Which offers better value, Claude Opus 4.6 or DeepSeek V4 Pro 0813?+
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.