Which is better, Claude Opus 4.5 or DeepSeek-V4-Pro?

Across 49 shared benchmarks tracked on Vector Wire, Claude Opus 4.5 leads on 18 and DeepSeek-V4-Pro leads on 30 — DeepSeek-V4-Pro leads on more. Strengths differ by axis; the table below shows every head-to-head number with provenance.

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Claude Opus 4.5 vs DeepSeek-V4-Pro

AnthropicvsDeepSeek49 shared benchmarks18–30 head-to-head

Benchmark	Claude Opus 4.5	DeepSeek-V4-Pro
AA Agentic Index	59.6	63.3
AA Intelligence	41.9	53
AA-LCR	76	70
AA-Omniscience	14	-10.6
aime_2026	95.1	96.7
arena_elo	1473	1457
arena_text_factuality	1458	1450
Artificial Analysis Coding Index	47.8	59.4
browsecomp	37	83.4
coding_arena_elo	1495	1582
critpt	4.6	13
cybergym	50.6	52.7
gdpval	47.3	49
GPQA Diamond	87	90.5
HLE	30.8	48.2
HLE (with tools)	43.4	48.2
hmmt_feb_2026	85.3	95.2
hmmt_nov_2025	93.3	94.4
IFBench	58	76.5
imo_answer_bench	84	89.8
livebench	76	73.6
livebench_agentic_coding	39.7	42.6
livebench_coding	79.7	70
livebench_data_analysis	74.4	74.5
livebench_instruction_following	62.5	62.4
livebench_language	81.3	78.1
livebench_math	90.4	90.7
livebench_reasoning	80.1	82.7
LiveCodeBench	87	93.5
MCP Atlas	69.8	74.2
MMLU-Pro	90	87.5
nl2repo	43.2	38.5
OmniScience Accuracy	46.6	43
OmniScience Non-Hallucination	39	12.2
scicode	50	50
simplebench	62	50.9
simpleqa_verified	41.8	57.9
SWE-bench Multilingual	77.5	76.2
SWE-bench Pro	57.1	55.4
SWE-bench Verified	81.5	80.6
Terminal-Bench 2.0	59.3	67.9
Terminal-Bench Hard	47	46.2
tool_decathlon	43.5	52.8
toolathlon	43.5	51.8
vectara_answer_rate	98.7	97.2
vectara_avg_summary_length	114.5	153.8
vectara_factual_consistency	89.1	91.4
vectara_hallucination_rate ↓	10.9	8.6
τ²-Bench Telecom (AA run)	89.5	96.2

Best tracked score per model per benchmark (default configuration; source-attributed). ↓ marks lower-is-better metrics. Open either model for its full surface, provenance and pricing.