GPT-6.1 Sol is the best AI for analysts. Analysis is about drawing conclusions from mixed signals, not restating them, and GPT-6.1 Sol reasons well about what the numbers do and do not support. It handles structured outputs for pulling data from reports, and its 1.05M-token window holds a quarter's worth of filings. For the very hardest quantitative questions, GPT-6 Astra is stronger; for digesting enormous source sets, Gemini 3.1 Pro.
The safest analysts default, the cheaper option worth trying first, and the specialist pick — before you read the detail below.
GPT-6.1 Sol is the strongest answer here for analysts — pick it when quality of output matters more than the $2.00/1M/1M input you pay for it.
Claude Sonnet 5.5 is the cheaper way in for analysts, at $2.00/1M/1M input against GPT-6.1 Sol's $2.00/1M/1M.
Gemini 3.1 Pro is the fastest of these for analysts — worth it when latency is what the reader notices, not the last few points of reasoning depth.
GPT-6.1 Sol is the strongest analyst model for its price.
Gemini 3.1 Pro is the better companion for long-context source digestion.
GPT-6 Astra is worth its $10/$50 price only on the hardest quantitative work.
Use GPT-6.1 Sol for interpretation, prioritisation and recommendations.
Use Gemini 3.1 Pro for large source sets and research-heavy analysis.
Use GPT-6 Astra when a modelling or maths problem is genuinely hard.
Switch the scoring lens to see whether the analysts answer changes when cost, speed, or long-document depth leads the decision.
Anthropic / Balanced / Oct 10, 2026
Near-Opus 5.5 quality on scoped work at half the price.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
The work is long, ambiguous and multi-step — Anthropic positions Opus 5.5 for exactly that — or you need the lowest possible price, where Haiku 5.5 costs a twentieth as much.
Where the analysts recommendation shifts once you weigh price or latency differently.
Near-Astra capability at Sol pricing — OpenAI's value pick.
Best for research and deep document analysis — 2M context at the best premium price.
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50.
Near-Opus 5.5 quality on scoped work at half the price.
List prices and published scores — the numbers this page's pick is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GPT-6.1 SolOpenAI | $2.00/1M | $10.00/1M | $40 | 1.1M tokens | Balanced | 98 | 94 | 97 |
| Gemini 3.1 ProGoogle | $2.00/1M | $12.00/1M | $44 | 2M tokens | Balanced | 80 | 82 | 99 |
| GPT-6 AstraOpenAI | $10.00/1M | $50.00/1M | $200 | 1.1M tokens | Deliberate | 100 | 97 | 100 |
| Claude Sonnet 5.5Anthropic | $2.00/1M | $10.00/1M | $40 | 1M tokens | Fast | 98 | 98 | 95 |
Scores out of 100 — how we evaluate models. “Est. month” is 10M in / 2M out at list price: a ceiling, no discounts.
Why each one is on the shortlist for analysts, what it is genuinely good at, and where we would steer you away from it.
The default answer for analysts — 98/100 on the coding axis, and the model we would start with unless the price below rules it out.
OpenAI's September 29, 2026 DevDay release — a Sol-tier reasoning model that OpenAI says comes close to GPT-6 Astra on agentic coding, computer use and professional work at one fifth of Astra's price.
You need it inside ordinary ChatGPT chats today, or your prompts regularly pass 272K tokens where the rate doubles.
OpenAI's best value for serious work. GPT-6.1 Sol replaces both GPT-6 Sol and, for most teams, GPT-6 Astra: independent testing has it a point behind Astra at a fifth of the list price. Pick Astra only when the last point of capability is worth five times the bill.
Full pricing, benchmark table and release notes on the GPT-6.1 Sol page.
The fastest model in this shortlist for analysts. Pick it when turnaround is what your readers or users notice.
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.
Your primary use case is writing quality or agentic coding — Claude wins both.
The best research and long-context model available. Handles entire codebases, legal documents, and large datasets in a single pass — at a lower price than GPT-5.4 or Claude Sonnet 4.6.
Full pricing, benchmark table and release notes on the Gemini 3.1 Pro page.
Also worth a look for analysts, at 100/100 on the coding axis.
OpenAI's frontier answer to Fable 5.1 — computer-use and agentic-coding leader at $10/$50. Full GPT-6 Astra review →
The cost-conscious pick for analysts, balanced-tier pricing than the top choice while holding 98/100 on coding.
Near-Opus 5.5 quality on scoped work at half the price. Full Claude Sonnet 5.5 review →
UseRightAI recommendations are based on practical decision factors people actually feel in day-to-day use.
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For analysts, GPT-6.1 Sol (OpenAI) is our pick. Near-Astra capability at Sol pricing — OpenAI's value pick. It costs $2/1M input and $10/1M output tokens, with a 1.05M-token context window — enough headroom for all but the largest analysts jobs. Gemini 3.1 Pro is the closest alternative if it doesn't fit your setup.
Because the work it is built for overlaps closely with analysts: coding agents in Codex that need near-Astra quality at Sol pricing and computer-use and browser automation run at volume. OpenAI's best value for serious work. GPT-6.1 Sol replaces both GPT-6 Sol and, for most teams, GPT-6 Astra: independent testing has it a point behind Astra at a fifth of the list price. Pick Astra only when the last point of capability is worth five times the bill.
On a moderate month — 10M input and 2M output tokens — GPT-6.1 Sol runs about $40.00 at list price, with no batch or caching discounts applied, so treat that as a ceiling. It is also the cheapest option among the models compared here, so for analysts there is no cost argument for dropping to something weaker.
Prompts above 272K input tokens are billed at $4/$15. At launch it was available in ChatGPT Work and Codex, not in regular ChatGPT conversations. Avoid it if you need it inside ordinary ChatGPT chats today, or your prompts regularly pass 272K tokens where the rate doubles. None of that rules it out for analysts on its own — but if one of those limits maps onto how you actually work, take the alternative on this page seriously rather than defaulting to the top pick.
Claude Sonnet 5.5, rated fast against GPT-6.1 Sol's balanced. Speed matters most for interactive and high-volume work; if your analysts runs in the background, the slower and more capable model is usually the better trade.