Best models for deep research

Hard questions where the answer is worth waiting for: reading a pile of sources, reasoning through them, writing something defensible. Here you want the model to think for as long as it needs. Latency is not a consideration and price rarely is either, because the alternative is a person spending an afternoon.

As of 11 Oct 2026, Claude Opus 5.5 at xhigh effort fits this best, with reasoning of 80 and knowledge of 81.

How this is weighted

30%Reasoningthe work is following a long chain of argument without dropping it
25%Qualitybroad capability, since research questions refuse to stay inside one category
25%Knowledgerecall that is right, and an unwillingness to invent what it does not know
20%Long contextthe sources have to fit, and the model has to still be paying attention at the end of them

368 of 434 ranked models qualify: the rest either miss one of the measurements the weighting depends on, or fall outside a limit above. We would rather leave a model out than score it on the dimensions it happens to have.

#	Model	Fit	Reasoning	Knowledge	Long context	Quality	Price per 1M
1	Claude Opus 5.5xhighAnthropic	99	80	81	68	69.5	$8.00
2	Claude Fable 5.1maxAnthropic	98	77	78	68	70.8	$20.00
3	GPT-6.1 SolhighOpenAI	97	79	80	66	67.9	$4.00
4	Claude Fable 5maxAnthropic	96	74	81	66	69.1	$20.00
5	GPT-6 AstraxhighOpenAI	96	81	81	65	69.2	$20.00
6	Muse Spark 1.3maxMeta	96	78	73	67	67.7	$2.00
7	Claude Opus 5xhighAnthropic	96	87	78	65	67.7	$10.00
8	Gemini 4 ArgonhighGoogle	95	82	76	65	70.0	$4.00
9	MiMo-V2.6-ProXiaomi	95	80	66	69	64.8	$0.548
10	Claude Sonnet 5.5maxAnthropic	94	81	65	67	67.6	$4.00
11	GPT-6 SolmaxOpenAI	94	72	70	67	65.6	$4.00
12	GPT-5.5xhighOpenAI	94	76	66	68	65.9	$11.25
13	GPT-5.6 SolmaxOpenAI	94	73	66	67	67.5	$8.00
14	GPT-5.4 ProOpenAI	94	73	74	–	63.6	$67.50
15	Step 5 PreviewStepFun	93	72	69	70	62.4	$1.43
16	Gemini 3.8 FlashmediumGoogle	92	63	75	67	64.6	$1.50
17	GPT-5.3-CodexxhighOpenAI	92	69	67	67	63.9	$4.81
18	Kimi K3maxMoonshot AI	91	67	63	70	65.5	$6.00
19	Muse Spark 1.1Meta	91	68	70	–	63.1	$2.00
20	Grok 4.6mediumSpaceXAI	90	65	74	66	64.2	$3.00
21	Gemini 3.7 FlashhighGoogle	90	68	68	66	63.0	$1.50
22	Qwen3.8 2.4T A95BAlibaba	90	75	64	65	63.3	$3.00
23	Claude Opus 4.6thinkingAnthropic	89	76	62	–	62.5	$10.00
24	Qwen3.8 MaxmaxAlibaba	89	72	63	65	64.2	$3.00
25	Gemini 3.1 ProGoogle	89	69	65	66	62.1	$4.50
26	Muse Spark 1.2xhighMeta	89	70	67	65	62.7	$2.00
27	GPT-5.4xhighOpenAI	88	70	60	66	64.2	$5.63
28	NewClaude Haiku 5.5xhighAnthropic	88	79	64	64	61.1	$0.200
29	GLM 5.3 FlashZhipu AI	88	67	65	65	62.2	$0.238
30	Claude Opus 4.8maxAnthropic	88	69	67	64	62.4	$10.00
31	GPT-5.6 TerramaxOpenAI	87	70	58	67	63.7	$4.50
32	Claude Opus 4.7Anthropic	87	65	62	–	63.7	$10.00
33	Grok 4.7highSpaceXAI	87	61	76	64	64.3	$3.00
34	Muse SparkMeta	87	66	64	64	64.6	–
35	DeepSeek V4.1 FlashmaxDeepSeek	86	65	59	67	61.8	$0.525
36	GLM 5.3maxZhipu AI	86	69	59	65	64.0	$2.15
37	Gemini 3.6 FlashhighGoogle	85	63	66	65	60.4	$1.50
38	DeepSeek V4 PromaxDeepSeek	85	65	60	65	62.8	$1.98
39	Qwen3 7maxAlibaba	84	66	63	65	59.9	$3.75
40	Gemini 3.5 FlashmediumGoogle	84	62	71	62	63.0	$3.38

How to read this

Fit is a percentile blend, not a score out of a hundred: each dimension is ranked against every other model that could be judged here, then combined with the weights above. It says how well a model matches this job compared with the alternatives — a model can fit voice work superbly and sit well down the quality leaderboard, which is the point of ranking by job rather than by index.

Disagree with the weighting? That is a reasonable thing to do, which is why it is printed rather than hidden. To set your own constraints instead, use the model finder.

Cite as: BenchLeader, “Best models for deep research”, https://www.benchleader.com/use/deep-research, data as of 11 Oct 2026.