Top recommendation

Best AI for Research

Research models need memory, synthesis, and the ability to connect threads without losing signal. These picks favor useful depth over empty speed.

Last verified: June 2026

/Rankings refresh daily when model data changes

Rankings refresh dailyScored on 6 criteriaNo paid rankings

Best pick right now

AnthropicPremium

Claude Fable 5

New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

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Cost in

$10.00/1M

Context

1M tokens

Speed

Deliberate

Why it wins

The top research pick handles large inputs and complex synthesis better than general alternatives.

Strong backups exist if you prefer speed, ideation, or better cost efficiency.

The ranking rewards document handling and reasoning quality, not just responsiveness.

Decision notes

Choose the top pick when context window and synthesis quality are both essential.

Choose a faster alternative when early-stage exploration matters more than depth.

Choose a hybrid model if research quickly turns into product decisions or implementation.

Interactive decision lab

Tune the best ai for research ranking

Use the controls to see how the recommendation changes when your workflow shifts toward quality, cost, speed, or long-context work.

#1Claude Fable 591 pts

#2Claude Mythos 590 pts

#3Claude Opus 4.890 pts

#4Gemini 3.1 Pro86 pts

#5OpenAI: o3 Deep Research62 pts

Quality first

Claude Fable 5

Anthropic / Premium / Jun 9, 2026

New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.

Cost

$10.00/1M

$50.00/1M out

Speed

Deliberate

2/100 score

Context

1M tokens

input window

View model

Data-backed recommendation

Avoid this pick if

You are latency- or cost-sensitive, or your tasks don't need frontier-level reasoning — Opus 4.8 at half the price is plenty.

Strengths

80.3% SWE-Bench Pro — the new #1, up from Opus 4.8's 69.2% and GPT-5.5's 58.6%

1932 on GDPval-AA, ahead of Opus 4.8 (1890) and GPT-5.5 (1769)

1M-token context at standard pricing, 128K max output per request

Mythos-class capability released for general use with new cyber-risk safeguards

Weaknesses

Priced at $10/$50 per 1M tokens — double Opus 4.8 ($5/$25)

Deliberate pace; not for latency-sensitive interactive apps

Standard-use safeguards block some high-risk security workloads (use Mythos 5 with partner access)

Ranked alternatives

Strong backups depending on your budget, workload, and preferred tradeoffs.

GooglePremium

Gemini 3.1 Pro

Google's flagship with the largest context window of any frontier model at 2M tokens, Deep Think reasoning, and the best price-to-performance among premium models.

Verdict

Best for research and deep document analysis — 2M context at the best premium price.

Quality score

89%

Pricing

$2.00/1M in

$12.00/1M out

Speed

Balanced

Best for research, deep document analysis, and long-context reasoning at competitive pricing

Context

2M tokens

The 2M context window is a genuine competitive advantage — no other frontier model gets close for document-heavy workflows.

Research leader2M contextBest value premiumDeep Think

Best for

Research, deep document analysis, and long-context reasoning at competitive pricing

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AnthropicPremium

Claude Mythos 5

Anthropic's most powerful frontier model — the same underlying model as Fable 5 with safeguards lifted in some areas, restricted to vetted enterprise and research partners. The capability ceiling of mid-2026.

Verdict

The frontier ceiling — same model as Fable 5, safeguards lifted, partner-only.

Quality score

98%

Pricing

$10.00/1M in

$50.00/1M out

Speed

Deliberate

Best for frontier cybersecurity research, autonomous vulnerability discovery, and the absolute capability ceiling

Context

1M tokens

Launched June 9, 2026 alongside Fable 5, following the April Project Glasswing private preview on Google Cloud. Restricted to vetted enterprise and research partners due to advanced cybersecurity capabilities. Same underlying model and benchmarks as Claude Fable 5.

FrontierRestricted accessCybersecuritySWE-Bench Pro #1Mythos-classPremiumNew

Best for

Frontier cybersecurity research, autonomous vulnerability discovery, and the absolute capability ceiling

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AnthropicPremium

Claude Opus 4.8

Anthropic's newest Opus flagship — 69.2% SWE-Bench Pro, 88.6% SWE-Bench Verified, 1890 Arena Elo (121 pts ahead of GPT-5.5), and native parallel subagents. Same $5/$25 price as Opus 4.7.

Verdict

New #1 on SWE-Bench Pro — parallel subagents, same price as Opus 4.7.

Quality score

97%

Pricing

$5.00/1M in

$25.00/1M out

Speed

Deliberate

Best for hardest coding tasks, parallel agentic workflows, and high-fidelity vision

Context

1M tokens

Launched May 27, 2026. Available on Claude API, AWS Bedrock, Google Vertex AI, Microsoft Foundry, and GitHub Copilot. Fast mode available at $10/$50 per 1M tokens.

Coding leaderSWE-bench Pro #1Parallel subagentsAgenticLong contextPremiumNew

Best for

Hardest coding tasks, parallel agentic workflows, and high-fidelity vision

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OpenAIPremium

OpenAI: o3 Deep Research

OpenAI's o3 Deep Research is a reasoning-heavy model purpose-built for multi-step research tasks, capable of autonomously browsing the web, synthesizing sources, and producing detailed analytical reports. It combines o3's chain-of-thought reasoning with agentic tool use to tackle complex, open-ended research questions.

Verdict

The gold standard for autonomous AI research — if you can afford to run it.

Quality score

67%

Pricing

$10.00/1M in

$40.00/1M out

Speed

Deliberate

Best for conducting exhaustive, multi-source research that would take a human analyst hours to compile manually.

Context

200k tokens

Deep Research mode involves agentic tool calls and web browsing, which can multiply effective token costs significantly. Pricing is per token but real-world research sessions often consume large amounts of both. Available via ChatGPT Plus/Pro and API; API access may require higher usage tiers.

Deep ResearchAgenticReasoningPremiumWeb Browsing

Best for

Conducting exhaustive, multi-source research that would take a human analyst hours to compile manually.

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How we evaluate AI models

UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.

Explore related decisions

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FAQ

What is the current top pick for best ai for research?

Claude Fable 5 is the current top recommendation because it delivers the strongest mix of fit, output quality, and practical usefulness for this category.

What if I need a cheaper option?

Google: Gemma 2 9B is the strongest lower-cost alternative when you want better value without dropping all the way down in usefulness.

How should I choose between the top recommendation and the alternatives?

Choose the top pick when you want the safest default. Choose an alternative when your priority shifts toward cost, speed, context window, or a more specialized workflow fit.

Which AI is cheapest for this kind of workflow?

Google: Gemma 2 9B is the cheapest strong alternative here if you want better value without dropping to a weak default.

Best AI for Research

Research models need memory, synthesis, and the ability to connect threads without losing signal. These picks favor useful depth over empty speed.

Last verified: June 2026

/Rankings refresh daily when model data changes

Rankings refresh dailyScored on 6 criteriaNo paid rankings

Best pick right now

AnthropicPremium

Claude Fable 5

New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.

View model

Cost in

$10.00/1M

Context

1M tokens

Speed

Deliberate

Why it wins

The top research pick handles large inputs and complex synthesis better than general alternatives.

Strong backups exist if you prefer speed, ideation, or better cost efficiency.

The ranking rewards document handling and reasoning quality, not just responsiveness.

Decision notes

Choose the top pick when context window and synthesis quality are both essential.

Choose a faster alternative when early-stage exploration matters more than depth.

Choose a hybrid model if research quickly turns into product decisions or implementation.