1stTop pick
Researched 32d agoGPT-5.6 Sol
- Context
- 1.05m
- Output (from)
- $30.00 / 1M
Best LLMs for Retrieval-Augmented Generation (2026)
Last refreshed 2026-07-26. Next refresh: weekly.
Best LLMs for RAG in 2026 — ranked by context window, retrieval benchmarks, and tool support. Covers document QA to enterprise search.
Verdict
Use GPT-5.6 Sol for RAG today.
GPT-5.6 Terra is the runner-up: 1.05m vs 1.05m on Context.
2ndShortlist
Researched 32d agoGPT-5.6 Terra
- Context
- 1.05m
- Output (from)
- $15.00 / 1M
3rdShortlist
Researched 32d agoGPT-5.6 Luna
- Context
- 1.05m
- Output (from)
- $6.00 / 1M
How we rank
RAG picks emphasize the strongest sourced long-document benchmark among tracked RAG needles, QA, and retrieval suites, then context window, then recency.
- Eligibility — Models tagged for the RAG decision task (collections/specialization fit or scores on RULER, ZeroSCROLLs, InfiniteBench, multi-needle, MS MARCO, SQuAD, NaturalQuestions, TriviaQA, etc.).
- Primary ranking — Best score across the RAG benchmark bundle, then larger declared context window, then newer release.
- Variant collapse — We keep one row per model family (`familySlug` + parameter tier). When headline scores tie within ±0.5 pt (±10 Elo on Chatbot Arena), we pick the canonical SKU by lowest tracked input price, then GA over preview or limited access, then newest `release`. A folded sibling within the benchmark noise band can show a "Tied within margin" chip on that score cell.
- Pricing — Lowest tracked provider input/output where present.
| # | Model | Input $/1M | Output $/1M | |
|---|---|---|---|---|
| 1 | Nemotron 3 Super-120B-A12B Signal used: RULER 96.33% | $0.09 | $0.45 | |
| 2 | Llama 4 Scout 17B-16E Instruct Vision Signal used: Context 10m | $0.08 | $0.22 | |
| 3 | Gemini 1.5 Pro Signal used: Context 2m | $1.25 | $5.00 | |
| 4 | GPT-5.6 Sol ReasoningVisionTools Signal used: Context 1.05m | $5.00 | $30.00 | |
| 5 | GPT-5.6 Terra ReasoningVisionTools Signal used: Context 1.05m | $2.50 | $15.00 | |
| 6 | GPT-5.6 Luna ReasoningVisionTools Signal used: Context 1.05m | $1.00 | $6.00 | |
| 7 | GPT-5.5 ReasoningVisionTools Signal used: Context 1.05m | $5.00 | $30.00 | |
| 8 | GPT-5.5 Pro ReasoningVisionTools Signal used: Context 1.05m | $30.00 | $180.00 | |
| 9 | GPT-5.4 ReasoningVisionTools Signal used: Context 1.05m | $2.50 | $15.00 | |
| 10 | GPT-5.4 Pro ReasoningVisionTools Signal used: Context 1.05m | $30.00 | $180.00 | |
| 11 | Gemini 3.6 Flash ReasoningVisionTools Signal used: Context 1.05m | $1.50 | $7.50 | |
| 12 | Gemini 3.5 Flash-Lite ReasoningVisionTools Signal used: Context 1.05m | $0.30 | $2.50 | |
| 13 | Kimi K3 ReasoningVisionTools Signal used: Context 1.05m | $3.00 | $15.00 | |
| 14 | Gemini 3.5 Flash ReasoningVisionTools Signal used: Context 1.05m | $1.50 | $9.00 | |
| 15 | Antigravity Agent PreviewReasoningVision Signal used: Context 1.05m | — | — | |
| 16 | Gemini 3.1 Flash-Lite VisionTools Signal used: Context 1.05m | $0.25 | $1.50 | |
| 17 | Xiaomi MiMo-V2.5-Pro Tools Signal used: Context 1.05m | $0.43 | $0.87 | |
| 18 | Xiaomi MiMo-V2.5 ReasoningVisionTools Signal used: Context 1.05m | $0.14 | $0.28 | |
| 19 | Gemini 2.5 Pro Computer Use Preview PreviewVisionTools Signal used: Context 1.05m | $1.25 | $10.00 | |
| 20 | GPT-4.1 VisionTools Signal used: Context 1.05m | $2.00 | $8.00 |
Honorable mentions
Next seats in this ranking. Lines below are from each model's stored description in LLMReference seed data—spot-check the model page before relying on a capability claim.
- #4GPT-5.5
GPT-5.5 is OpenAI's fully retrained agentic model, released April 23, 2026. Optimised for agentic coding, computer use, knowledge work, and early scientific research. Achieves 82.7% on Terminal-Bench 2.0 (Codex CLI scaffold), 84.9% on GDPval, 58.6% on SWE-Bench Pro, 93.6% on GPQA Diamond, and 82.6% on SWE-Bench Verified (Vals.ai independent harness). Knowledge cutoff December 2025. Supports reasoning effort levels (none/low/medium/high/xhigh). Context window 1,050,000 tokens with a long-context surcharge above 272K tokens. Model ID: gpt-5.5.
1.05m
Context
GPT-5.5 Pro is OpenAI's premium extra-compute deployment of GPT-5.5, released April 23, 2026. It uses the same underlying weights as GPT-5.5 standard with additional parallel test-time compute for harder tasks. Supports text and image inputs, reasoning effort control, tool use, structured outputs, code execution, a 1,050,000-token context window, and 128K max output. Key datapack rows: Terminal-Bench 2.1 78.2%, SWE-bench Pro 58.6%, GPQA Diamond 93.6%, ARC-AGI-2 high effort 83.3%, BrowseComp Pro compute 90.1%, and FrontierMath Tier 4 39.6%. Official pricing is $30/M input, $180/M output, $10/M batch input, and $45/M batch output; native cached input discount is not listed.
1.05m
Context
- #6GPT-5.4
GPT-5.4 is OpenAI's flagship frontier reasoning model, released March 5, 2026. It incorporates advances from GPT-5.3-Codex for coding and agentic workflows, and adds 'Thinking' mode with editable reasoning plans. Key capabilities include computer use (navigating interfaces via Playwright), image understanding and generation integration, full-stack web app generation, tool calling, and deep research. Knowledge cutoff is August 31, 2025. Model ID: gpt-5.4.
1.05m
Context
Compare Top Picks
Side-by-side comparison of the top picks by price, benchmark, and API access.
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Frequently asked questions
Which LLM is best for RAG?
GPT-5.6 Sol is the current LLMReference top pick for RAG. The verdict uses the stored category signal Context: 1.05m. Output pricing starts at $30.00 per 1M tokens. Review the linked model and provider pages before production use because availability and pricing can change.
How does GPT-5.6 Sol compare to GPT-5.6 Terra for RAG?
GPT-5.6 Sol leads GPT-5.6 Terra in the visible shortlist on Context: 1.05m versus 1.05m. The pricing cards show GPT-5.6 Sol: output pricing starts at $30.00 per 1m tokens and GPT-5.6 Terra: output pricing starts at $15.00 per 1m tokens.
How does LLMReference rank LLMs for RAG?
LLMReference ranks LLMs for RAG from stored model, benchmark, freshness, and pricing data. The current methodology summary is: RAG picks emphasize the strongest sourced long-document benchmark among tracked RAG needles, QA, and retrieval suites, then context window, then recency.
How often is this list updated?
The LLM rankings on this page are updated daily as new benchmark scores, provider availability, and pricing data are tracked. The "as of" date at the top of the page shows the most recent refresh.
How do you decide which models appear in the top 3?
The podium picks are driven by the primary benchmark signal for this category (shown in the Methodology section), filtered to non-deprecated models with confirmed API availability. In ties, we prefer the more recently released model.
Are preview or beta models included?
Preview models appear in the "Watch list" section but are not in the main ranked podium unless the category explicitly allows it (e.g., /best/coding and /best/agents, where preview models often lead benchmarks).
Can I compare two specific models head-to-head?
Yes — use the Compare tool at llmreference.com/compare for a side-by-side breakdown of context window, pricing, benchmarks, and provider availability.
Is the pricing data real-time?
Pricing is tracked from provider documentation and updated regularly. It reflects the best available public data, not live API quotes — always verify before billing.