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Model comparison

Claude Opus 4.5 vs Deepgram Aura-2

Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Claude Opus 4.5

Anthropic

63.4/100

Supported · Public rank #39

90% interval 50.2–76.6

Deepgram Aura-2

Deepgram

—

Evidence status unavailable

90% interval unavailable

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 based on different benchmark sets are marked directional and do not name a winner.

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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Not enough matched evidence

    A complete context comparison is not sourced.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • 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. Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate. Deepgram Aura-2 has no comparable published API token rate.

    Confidence: rate-fallback

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    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
Claude Opus 4.5 only
45
Deepgram Aura-2 only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
Claude Opus 4.5
62.6
Deepgram Aura-2
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude Opus 4.5
71.7
Deepgram Aura-2
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Opus 4.5
64.4
Deepgram Aura-2
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 4.5
58.1
Deepgram Aura-2
Not measured
Weighted basis
4 vs 0 rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.5
57.5
Deepgram Aura-2
Not measured
Weighted basis
4 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.5
85.7
Deepgram Aura-2
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 4.5
69.9
Deepgram Aura-2
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.5
69.5
Deepgram Aura-2
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

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

Claude Opus 4.5
$0.0175
Fits in one request
Deepgram Aura-2
API rate not published
Fit state unavailable

Deepgram Aura-2 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.5
$0.325
Fits in one request
Deepgram Aura-2
API rate not published
Fit state unavailable

Deepgram Aura-2 has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Opus 4.5
$1.35
Does not fit in one request
Cached input priced at the published list-input rate
Deepgram Aura-2
API rate not published
Fit state unavailable
Cached-input rate unavailable

Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate. Deepgram Aura-2 has no comparable published API token rate.

Specification differences

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

Context window

Maximum documented context; output-token limits may be lower.

Claude Opus 4.5

200K

Deepgram Aura-2

N/A

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Opus 4.5

Not published

Deepgram Aura-2

No comparable hosted API rate

Deepgram model documentation

Documented inputs

Claude Opus 4.5

Not sourced

Deepgram Aura-2

Not sourced

Documented outputs

Claude Opus 4.5

Not sourced

Deepgram Aura-2

Not sourced

Provider availability

Claude Opus 4.5

Not sourced

Deepgram Aura-2

Not sourced

Reasoning profile

Claude Opus 4.5

Non-Reasoning

Deepgram Aura-2

Non-Reasoning

Weight access

Claude Opus 4.5

Proprietary

Deepgram Aura-2

Proprietary

License

Claude Opus 4.5

Proprietary

Deepgram Aura-2

Proprietary

Release date

Claude Opus 4.5

2025-11-01

Deepgram Aura-2

Not sourced

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
A complete documented context comparison is not available.

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 evidence45 rows

Agentic

  • Terminal-Bench 2.0

    Claude Opus 4.559.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.566.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • OSWorld

    Claude Opus 4.566.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • Claw-Eval

    Claude Opus 4.559.6%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • QwenClawBench

    Claude Opus 4.552.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • τ³-bench results

    Claude Opus 4.570.2%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • VITA-Bench

    Claude Opus 4.523.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • DeepPlanning

    Claude Opus 4.526.4%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • Toolathlon

    Claude Opus 4.543.5%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.542.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • MCP-Tasks

    Claude Opus 4.571.8%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • WideResearch

    Claude Opus 4.576.4%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • CyberGym

    Claude Opus 4.550.6%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • Gert Labs

    Claude Opus 4.564.23%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • JobBench

    Claude Opus 4.532.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.580.9%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • LiveCodeBench v6

    Claude Opus 4.584.8%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.557.1%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • SWE Multilingual

    Claude Opus 4.577.5%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • NL2Repo

    Claude Opus 4.543.2%
    Source
    Deepgram Aura-2—

    Not directly comparable

Reasoning

  • LongBench v2

    Claude Opus 4.564.4%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • AI-Needle

    Claude Opus 4.574%
    Source
    Deepgram Aura-2—

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.587%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • SuperGPQA

    Claude Opus 4.570.6%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • MMLU-Pro

    Claude Opus 4.589.5%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • MMLU-Redux

    Claude Opus 4.596.6%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • C-Eval

    Claude Opus 4.592.2%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • HLE

    Claude Opus 4.530.8%
    Source
    Deepgram Aura-2—

    Not directly comparable

Math

  • AIME26

    Claude Opus 4.595.1%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • HMMT Feb 2025

    Claude Opus 4.592.9%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • HMMT Nov 2025

    Claude Opus 4.593.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • HMMT Feb 2026

    Claude Opus 4.585.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • MMAnswerBench

    Claude Opus 4.584.0%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.520.690%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.54.167%
    Source
    Deepgram Aura-2—

    Not directly comparable

Multilingual

  • MMLU-ProX

    Claude Opus 4.585.7%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • NOVA-63

    Claude Opus 4.556.7%
    Source
    Deepgram Aura-2—

    Not directly comparable

Multimodal

  • MMMU-Pro

    Claude Opus 4.570.6%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • MathVision

    Claude Opus 4.574.3%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • CharXiv

    Claude Opus 4.568.5%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • VideoMMMU

    Claude Opus 4.584.4%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • ScreenSpot Pro

    Claude Opus 4.545.7%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • V*

    Claude Opus 4.567.0%
    Source
    Deepgram Aura-2—

    Not directly comparable

Instruction following

  • IFEval

    Claude Opus 4.590.9%
    Source
    Deepgram Aura-2—

    Not directly comparable

  • IFBench

    Claude Opus 4.558%
    Source
    Deepgram Aura-2—

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.5 or Deepgram Aura-2?

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, Claude Opus 4.5 or Deepgram Aura-2?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Opus 4.5 or Deepgram Aura-2?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Opus 4.5 or Deepgram Aura-2?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Claude Opus 4.5 or Deepgram Aura-2?

A complete documented context-window comparison is not available.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 4, 2026

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