Top recommendation

Best Long Context AI

Long-context AI matters when your work actually needs it. These picks are for teams reading huge docs, giant transcripts, and complex product context.

Last verified: June 2026

/Rankings refresh daily when model data changes

Rankings refresh dailyScored on 6 criteriaNo paid rankings

Best pick right now

GooglePremium

Gemini 3.1 Pro

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

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Cost in

$2.00/1M

Context

2M tokens

Speed

Balanced

Best overall

Gemini 3.1 Pro

Best budget

Mistral: Mistral Nemo

Best long-context

Claude Fable 5

Why it wins

The top long-context pick stays coherent across very large inputs.

Lower-cost alternatives help if you need more volume without flagship pricing.

The ranking rewards useful long-window reasoning, not just headline token counts.

Decision notes

Choose the top pick when long inputs and synthesis quality are equally important.

Choose a budget alternative if you need a large window without premium cost.

Choose a premium reasoning model if your context is large but not truly enormous.

Interactive decision lab

Tune the best long context ai 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

#3Gemini 3.1 Pro86 pts

#4Google: Gemini 2.5 Pro84 pts

#5Google: Gemini 2.5 Pro Preview 05-0683 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

2M token context window — the largest of any frontier model

Leads ARC-AGI-2 reasoning benchmark at 77.1%

Best price-to-performance among premium models at $2/$12 per 1M tokens

Weaknesses

Slower than Flash for everyday lightweight tasks

Claude Sonnet 4.6 is better for writing quality

Ranked alternatives

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

AnthropicPremium

Claude Fable 5

Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.

Verdict

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

Quality score

98%

Pricing

$10.00/1M in

$50.00/1M out

Speed

Deliberate

Best for the hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning

Context

1M tokens

Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses.

Coding leaderSWE-Bench Pro #1Mythos-classParallel subagentsAgenticLong contextPremiumNew

Best for

The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning

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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

View model

GoogleBalanced

Google: Gemini 2.5 Pro

Gemini 2.5 Pro is Google's flagship reasoning-capable model with a massive 1M token context window, designed for complex analysis, coding, and multimodal tasks. It balances frontier-level intelligence with competitive mid-tier pricing.

Verdict

The best Google model for serious, complex work — especially when you need to fit an entire codebase or document corpus into a single prompt.

Quality score

87%

Pricing

$1.25/1M in

$10.00/1M out

Speed

Balanced

Best for deep reasoning over very long documents, complex codebases, or multimodal inputs where context size is a constraint with other models.

Context

1.0M tokens

Pricing shown is for prompts under 200K tokens; inputs over 200K tokens are billed at $2.50/1M input and $15/1M output. Gemini 2.5 Pro includes built-in 'thinking' (reasoning) mode which can increase latency and cost further.

FlagshipLong ContextMultimodalReasoningGoogle

Best for

Deep reasoning over very long documents, complex codebases, or multimodal inputs where context size is a constraint with other models.

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GoogleBalanced

Google: Gemini 2.5 Pro Preview 05-06

Gemini 2.5 Pro Preview 05-06 is Google's latest frontier reasoning model featuring a massive 1M token context window and strong multimodal capabilities. It targets developers and researchers needing deep analytical power with competitive pricing relative to its capability tier.

Verdict

The go-to model when you need a frontier brain and a million-token memory, at a price that won't immediately break your budget.

Quality score

86%

Pricing

$1.25/1M in

$10.00/1M out

Speed

Deliberate

Best for complex multi-document analysis, long-context reasoning, and advanced coding tasks where a massive context window is essential.

Context

1.0M tokens

This is a preview model (05-06 date suffix indicates a versioned snapshot); Google may deprecate or change it without long notice. Confirm production readiness before building critical pipelines on this endpoint. The 1M context window applies to text and multimodal inputs combined.

Long ContextReasoningMultimodalFrontierPreview

Best for

Complex multi-document analysis, long-context reasoning, and advanced coding tasks where a massive context window is essential.

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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 long context ai?

Gemini 3.1 Pro 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?

Mistral: Mistral Nemo 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?

Mistral: Mistral Nemo is the cheapest strong alternative here if you want better value without dropping to a weak default.

Best Long Context AI

Long-context AI matters when your work actually needs it. These picks are for teams reading huge docs, giant transcripts, and complex product context.

Last verified: June 2026

/Rankings refresh daily when model data changes

Rankings refresh dailyScored on 6 criteriaNo paid rankings

Best pick right now

GooglePremium

Gemini 3.1 Pro

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

View model

Cost in

$2.00/1M

Context

2M tokens

Speed

Balanced

Why it wins

The top long-context pick stays coherent across very large inputs.

Lower-cost alternatives help if you need more volume without flagship pricing.

The ranking rewards useful long-window reasoning, not just headline token counts.

Decision notes

Choose the top pick when long inputs and synthesis quality are equally important.

Choose a budget alternative if you need a large window without premium cost.

Choose a premium reasoning model if your context is large but not truly enormous.