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BenchLM
OpenAI logo
Model A
GPT-6 Astra

OpenAI

84.08/100

Estimated · Public rank #2

90% interval 78.3–89.8

GPT-6 Astra vs GPT Realtime 2.1 Mini

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

OpenAI logo
Model B
GPT Realtime 2.1 Mini

OpenAI

—

Evidence status unavailable

90% interval unavailable

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    GPT-6 Astra

    GPT-6 Astra has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    GPT Realtime 2.1 Mini

    GPT Realtime 2.1 Mini has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    GPT Realtime 2.1 Mini

    GPT Realtime 2.1 Mini has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    GPT Realtime 2.1 Mini is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    GPT Realtime 2.1 Mini is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. GPT Realtime 2.1 Mini does not fit this workload in one request.

    Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
0
GPT-6 Astra only
25
GPT Realtime 2.1 Mini only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Not comparable
GPT-6 Astra
70.4
Supported · #5/152
GPT Realtime 2.1 Mini
Not ranked
Basis
BenchAlign lane · 9 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
GPT-6 Astra
74.6
Supported · #4/151
GPT Realtime 2.1 Mini
Not ranked
Basis
BenchAlign lane · 3 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
GPT-6 Astra
89.5
#1/20
GPT Realtime 2.1 Mini
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
GPT-6 Astra
82.2
Supported · #4/183
GPT Realtime 2.1 Mini
Not ranked
Basis
BenchAlign lane · 4 vs 0 public rows
Reading
Not comparable

Math

Not comparable
GPT-6 Astra
85.2
Unranked · 1 rankable row
GPT Realtime 2.1 Mini
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
GPT-6 Astra
Not ranked
GPT Realtime 2.1 Mini
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
GPT-6 Astra
82.8
Unranked · 3 rankable rows
GPT Realtime 2.1 Mini
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
GPT-6 Astra
Not ranked
GPT Realtime 2.1 Mini
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

GPT-6 Astra
$0.035
Fits in one request
GPT Realtime 2.1 Mini
$0.0018
Fits in one request

GPT Realtime 2.1 Mini has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

GPT-6 Astra
$0.65
Fits in one request
GPT Realtime 2.1 Mini
$0.0372
Fits in one request

GPT Realtime 2.1 Mini has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

GPT-6 Astra
$0.9
Fits in one request
GPT Realtime 2.1 Mini
$0.048
Does not fit in one request

GPT Realtime 2.1 Mini does not fit this workload in one request.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Reasoning profile

GPT-6 Astra

Reasoning

GPT Realtime 2.1 Mini

Non-Reasoning

Weight access

GPT-6 Astra

Proprietary

GPT Realtime 2.1 Mini

Proprietary

License

GPT-6 Astra

Proprietary

GPT Realtime 2.1 Mini

Proprietary

Release date

GPT-6 Astra

2026-09-03

GPT Realtime 2.1 Mini

2026-07-06

If you already use one of these models
Deployment change
Both entries list OpenAI as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.65 vs $0.0372. Cache-heavy agent loop: $0.9 vs $0.048.
Context tradeoff
GPT-6 Astra has the larger documented window (1.05M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence25 rows

Agentic

  • BrowseComp

    GPT-6 Astra91.5%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • OSWorld 2.0

    GPT-6 Astra72.6%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • Terminal-Bench 4.0

    GPT-6 Astra57.90%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    GPT-6 Astra64.6%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • ExploitGym

    GPT-6 Astra42.4%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • Agents' Last Exam

    GPT-6 Astra59.3%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • AutomationBench

    GPT-6 Astra41.4%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • HLE w/ tools

    GPT-6 Astra57.2%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    GPT-6 Astra87.3%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

Coding

  • DeepSWE

    GPT-6 Astra74.1%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • FrontierCode 1.1 Main

    GPT-6 Astra53.3%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • FrontierCode 1.1 Extended

    GPT-6 Astra64.5%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

Reasoning

  • ARC-AGI-1

    GPT-6 Astra98.50%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • ARC-AGI-2

    GPT-6 Astra95%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • ARC-AGI-3

    GPT-6 Astra62.7%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • GeneBench-Pro

    GPT-6 Astra37.8%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • MRCR v2 256K-512K

    GPT-6 Astra100.0%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • MRCR v2 512K-1M

    GPT-6 Astra96.3%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

Knowledge

  • GPQA

    GPT-6 Astra96%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • GPQA-D

    GPT-6 Astra96.0%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • HealthBench Professional

    GPT-6 Astra63.4%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • HealthBench Hard

    GPT-6 Astra36.3%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

Math

  • FrontierMath v2 (Tier 4)

    GPT-6 Astra97.600%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

Multimodal

  • ScreenSpot Pro

    GPT-6 Astra92.7%
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    GPT-6 Astra0.959
    Source
    GPT Realtime 2.1 Mini—

    Not directly comparable

Frequently asked questions

Which is better, GPT-6 Astra or GPT Realtime 2.1 Mini?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, GPT-6 Astra or GPT Realtime 2.1 Mini?

GPT Realtime 2.1 Mini is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, GPT-6 Astra or GPT Realtime 2.1 Mini?

GPT Realtime 2.1 Mini is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, GPT-6 Astra or GPT Realtime 2.1 Mini?

For the stated presets, chat costs $0.035 on GPT-6 Astra and $0.0018 on GPT Realtime 2.1 Mini; repository review costs $0.65 and $0.0372; the cache-heavy agent loop costs $0.9 and $0.048. GPT Realtime 2.1 Mini does not fit this workload in one request.

Which has the larger context window, GPT-6 Astra or GPT Realtime 2.1 Mini?

GPT-6 Astra has the larger documented context window: 1.05M, compared with 128K.

Related comparisons

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Last updated September 10, 2026

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