AI4SCIENCE · MODEL CAPABILITIES & RESEARCH TOOLS

Model capabilities & research tools

Choose models by capability and cost. Compare research tools by task.

Sources ↗Method ↗Checked 2026.10.08

Science & mathematics reasoning index Beta

7 model configurations · Ordered by composite score. Similar point estimates do not establish a reliable winner. Benchmark source ↗

Model / effortRun start dates · Full records in data sourcesBeta · 0–100GPQADiamond · %FrontierMathv2 · Tiers 1–3 · %InputUSD / 1M tokensOutputUSD / 1M tokensCache readUSD / 1M tokensUSD · Fixed usage
OpenAI · max Pre-releaseRun 2026.08.30
94.995.7793.6810501$20.00
OpenAI · max Run 2026.09.29
94.795.3993.682100.1$4.00
Anthropic · max Run 2026.09.29
92.995.5888.772100.1$4.00
Anthropic · max Run 2026.09.22
90.890.5991.234200.2$8.00
Google DeepMind · high Run 2026.09.02
84.695.3968.420.753.750.075$1.50
Alibaba · xhigh Run 2026.09.02
81.692.3065.6126Not published$3.00
xAI · xhigh Run 2026.09.22
76.892.7452.98260.5$3.00

Select a model for sources and conditions

Sol’s reference cost is one fifth of Astra’s, with similar point scores. This comparison applies only to these two benchmarks and fixed usage; it establishes neither statistical superiority nor best value in every setting.

Scoring method & scope

Composite = 60% GPQA + 40% FrontierMath · Science questions and mathematics only · Code, literature and workflows excluded.

Data & pricing sources

Official tariffs and special conditions are grouped below. The JSON preserves each original mean, SE, Started at, record ID and complete billing conditions; results were not independently rerun. Download full data JSON ↓

Epoch ↗ · GPQA Diamond ↗ · FrontierMath v2 ↗

ModelOfficial sourcesSpecial billing · USD / 1M tokens
GPT-6 AstramaxAPI ↗ · Cache ↗Cache write $12.5 / 30m · USD/1M
Long context: input_tokens > 272000 → $20 / $75.0 input/output
Regional option ×1.1
GPT-6.1 SolmaxAPI ↗ · Cache ↗Cache write $2.5 / 30m · USD/1M
Long context: input_tokens > 272000 → $4 / $15.0 input/output
Regional option ×1.1
Claude Sonnet 5.5maxAPI ↗ · Cache ↗Cache write $2.5 / 5m / $4 / 1h · USD/1M
No long-context premium
Regional option ×1.1
Claude Opus 5.5maxAPI ↗ · Cache ↗Cache write $5 / 5m / $8 / 1h · USD/1M
No long-context premium
Regional option ×1.1
Gemini 3.8 FlashhighAPI ↗ · Cache ↗Cache storage $0.5 / 1M / h
Introductory rate through 2026-12-31; future tariff in JSON
Qwen3.8 Max 0902xhighAPI ↗ · Cache ↗Cache write Explicit $2.5 / 5m; implicit $2 · USD/1M
Singapore / International; regional alternatives and unpublished cache-read rates in JSON
Grok 4.7xhighAPI ↗ · Cache ↗Long context: prompt_tokens >= 200000 in main pricing table → $4 / $12 input/output
Regional option ×1.1
Other evaluations · Research code, literature & workflows

Original evidence and historical references are retained below. They are excluded from this reasoning index; different tasks, older models and model + agent systems are not ranked together.

Research workflows · Workflow results

Research workflowsTerminal-Bench Science 0.1 · Run dates unverified

Original source ↗
No verified current-model result for this index

Current system results for GPT-6 Astra, Opus 5.5 and others exist, but public metadata lack actual run dates and immutable snapshots. They are excluded from this reasoning index.

Current official leaderboard ↗
Current-model source records · Run dates unverified

All three public system results use 70 tasks × three trials. Table creation/update dates and model-release dates are kept separately and are not treated as run dates.

Source model + agentOriginal resolve rate ± SEActual run dateRecord date
GPT-6 Astra
Codex · max
68.1% ± 3.2Not published2026-09-22
Leaderboard record created
Opus 5.5
Claude Code · max
63.3% ± 3.3Not published2026-09-23
Leaderboard record created
Fable 5.1
Claude Code · max
40.0% ± 3.4Not published2026-09-13
Leaderboard record created
Official leaderboard ↗

Source leaderboard updated 2026-09-23. Record creation, modification and model-release dates do not prove a rerun. Codex / Claude Code system results are not scores for the underlying model alone.

Historical references · Collapsed by default

Older models and snapshots are retained as historical evidence and excluded from current-model comparisons.

Research workflowsTerminal-Bench Science 0.1 · Three older-system results

Stanford / Harbor · Leaderboard ↗
70 tasks · Three trials per task · Native agent systemsPage checked: 2026-10-08 · Run dates unlisted
Model / providerAgent / effortOriginal resolve rate ± SE ↑Model release dateSource / conditions
Anthropic · Official table name
Claude Code
Effort: max
30.0% ± 3.22026-07-24
Model release date
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official results ↗
OpenAI · Official table name
Codex
Effort: max
22.4% ± 2.92026-07-09
Model release date
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official results ↗
Anthropic · Official table name
Claude Code
Effort: max
21.4% ± 2.82026-06-09
Model release date
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official results ↗

Scroll horizontally for configurations and sources →

These are model + agent workflow results; Claude Code and Codex configurations are kept separately. SE is the source’s standard error. Actual run and leaderboard-update dates are unlisted; page-check dates are separate. The protocol is distinct from AA / Vals mini-swe-agent. Source Cost is the entire evaluation bill and is not converted to USD/task. These results do not rank underlying models alone.

Scientific code · Code evaluations

Scientific codeSciCode · Current results unverified

Original source ↗
No verified current-model result for this index

The original leaderboard’s new-result announcements remain in 2025. Recent external reruns require separate protocol, run-date and usage-permission verification.

Original protocol & historical leaderboard ↗

Original SciCode, AA v1.0.1 and SciCode-Verified remain separate. Older o3-mini / o1 / Claude 3.5 scores are excluded from the current table.

Historical references · Collapsed by default

Older models and snapshots are retained as historical evidence and excluded from current-model comparisons.

Scientific codeOriginal SciCode · Six official historical results

SciCode · Official table ↗
Main problems / subproblems shown separately · Original historical table2025-02-01 announcement added o3-mini / DeepSeek; run dates unlisted
Model / providerMain-problem resolve rate ↑Subproblems ↑Source / conditions
OpenAI · Original table ID
10.8%33.3%
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official table ↗
OpenAI · Original table ID
9.2%34.4%
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official table ↗
OpenAI · Original table ID
9.2%33.0%
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official table ↗
OpenAI · Original table ID
7.7%28.5%
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official table ↗
DeepSeek · Original table ID
4.6%28.5%
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official table ↗
Anthropic · Original table ID
4.6%26.0%
Sources & conditions

Configurations, metrics and dates follow the original row fields. Unpublished model snapshots and run dates remain unknown. Full protocol conditions appear below the table.

Official table ↗

Scroll horizontally for configurations and sources →

The original table remained visible on 2026-10-08. It is not a complete current-model leaderboard for 2026. SciCode-AA v1.0.1 and SciCode-Verified remain separate; scores are neither substituted nor combined.

Literature & analysis · Evaluations

Literature & analysisAstaBench · Current-model results unverified

Original source ↗
No verified current-model result for this index

The official public test-submission directory has 85 files; the latest submission is 2026-08-24. Newer submissions use custom agents and models, without verified run evidence supporting direct comparison with fixed current GPT / Claude configurations.

Later public submissions ↗

August 24 is submit_time, not generation or run date. Spring judge changes and rescoring old outputs do not establish a new-model rerun.

Historical references · Collapsed by default

Older models and snapshots are retained as historical evidence and excluded from current-model comparisons.

Literature & analysisAstaBench · Two official spring snapshots

Ai2 · Official snapshot ↗
Suite 1.0.0 · ReAct · Source’s original Overall metricSnapshot published: 2026-04-30 · Task run dates unlisted
Model + framework / providerVersion / configurationOriginal Overall ↑LLM cost / taskSource / conditions
Anthropic · Model + ReAct framework
suite 1.0.0
max · adaptive thinking
58.0%3.54USD/task
Sources & conditions

Ai2’s official 2026-04-30 update reports these ReAct results and average LLM costs. Some judges changed and results were rescored; reevaluating old outputs is not a model rerun. This snapshot is not October’s current champion.

Official snapshot ↗Later public submissions ↗
OpenAI · Model + ReAct framework
suite 1.0.0
xhigh reasoning
52.9%1.61USD/task
Sources & conditions

Ai2’s official 2026-04-30 update reports these ReAct results and average LLM costs. Some judges changed and results were rescored; reevaluating old outputs is not a model rerun. This snapshot is not October’s current champion.

Official snapshot ↗Later public submissions ↗

Scroll horizontally for configurations and sources →

Only clearly sourced spring records are shown; later submissions are not exhaustively aggregated. Overall is Asta’s own metric, not a cross-benchmark research score. LLM costs cover this run’s model calls, excluding total compute, retrieval, storage and human work.

Capability & API pricing sources

Epoch official data ↗ · The two original benchmark scores and 60 / 40 weights are unchanged. Source package updated 2026.10.08; actual run starts, configurations and record IDs appear in Data & pricing sources. Epoch’s internal score data are used under CC BY 4.0, which does not cover questions or external data. We did not independently rerun the benchmarks.
API prices come from official provider documentation, checked 2026.10.08. Fixed usage is 750,000 uncached input + 250,000 output tokens, including reasoning. Model-specific conditions appear in Data & pricing sources. Commercial API tariffs are not benchmark invoices.

Tool inclusion & scope

Five research tasks compare candidate features, free allowances and relevant paid tiers. Current pricing and public evidence for eight tools were checked. The 18-entry directory retains other entry points. Tools do not inherit their underlying model scores.
This is a static 2026.10.08 snapshot. Research code, literature and workflow evidence is retained under Other evaluations and excluded from this index.