Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Auto Router (Beta) vs DeepSeek V4 Pro benchmark

Name: Auto Router (Beta) vs DeepSeek V4 Pro AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Auto Router (Beta) (openrouter) and DeepSeek V4 Pro (DeepSeek) using the latest snapshots we have as of Aug 17, 2026. Auto Router (Beta) wins on output price at $-1,000,000/1M. Auto Router (Beta) has the larger context window (2M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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openrouter

Auto Router (Beta)

Auto-discovered from OpenRouter (openrouter/auto-beta). Preview until a second source matches.

$-1000000/1M out

DeepSeek

DeepSeek V4 Pro

Open-weight-adjacent DeepSeek flagship. High reasoning density per dollar.

Elo 1,536$3.9600000000000004/1M out

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Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Auto Router (Beta) (3)vsDeepSeek V4 Pro (7)

Auto Router (Beta): 3W (30%)Overall: DeepSeek V4 ProDeepSeek V4 Pro: 7W (70%)

← Auto Router (Beta)DeepSeek V4 Pro →

DeepSeek V4 Pro (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,536

Coding Elo

—vs1,544

SWE-bench

—vs71.6%

LiveBench

—vs70.1%

GPQA Diamond

—vs84%

Auto Router (Beta): 0WDeepSeek V4 Pro: 5W

DeepSeek V4 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs70 tok/s

Time to first token

—vs410 ms

Auto Router (Beta): 0WDeepSeek V4 Pro: 2W

Auto Router (Beta) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$-1,000,000/1Mvs$3.96/1M

Input price

$-1,000,000/1Mvs$1.32/1M

Context window

2Mvs1M

Auto Router (Beta): 3WDeepSeek V4 Pro: 0W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageDeepSeek V4 Pro 4/6

Preference Elo

No shared data

Throughput Speed

No shared data

Price Efficiency

Auto Router (Beta)

$1000003.96/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,536

Code Elo

High is better

—

Code EloHigh is better

1,544

LiveBench

High is better

—

LiveBenchHigh is better

70.1%

SWE-bench

High is better

—

SWE-benchHigh is better

71.6%

GPQA

High is better

—

GPQAHigh is better

84%

TTFT

Low is better

—

TTFTLow is better

410 ms

Speed

High is better

—

SpeedHigh is better

70 tok/s

In $

Low is better

$-1,000,000/1M

In $Low is better

$1.32/1M

Out $

Low is better

$-1,000,000/1M

Out $Low is better

$3.96/1M

Context

High is better

+91%2M

ContextHigh is better

Key Selection Recommendations

1
Auto Router (Beta):Pick Auto Router (Beta) when you are optimizing output cost.
2
Auto Router (Beta):Pick Auto Router (Beta) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatAuto Router (Beta)

Lower output list price ($-1,000,000/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAuto Router (Beta)

Larger window (2M).

Screenshots / visionDeepSeek V4 Pro

DeepSeek V4 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Auto Router (Beta)	Lower output list price ($-1,000,000/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Auto Router (Beta)	Larger window (2M).
Screenshots / vision	DeepSeek V4 Pro	DeepSeek V4 Pro is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

compareJun 13, 2026

DeepSeek vs Claude: the cheap-versus-frontier question, remapped

Top DeepSeek vs top Anthropic Elo. Usually V4 Pro vs Opus 5. License and invoice decide as much as Elo.

launchJun 12, 2026

DeepSeek V4 Pro: high reasoning density per dollar

2026-06 open-weight-adjacent flagship. The usual cheap-vs-Claude question starts here.

launchJan 20, 2025

DeepSeek R1 stays as the open-weights RL baseline

Jan 2025 reasoning model. Still searched. V4 Pro is the newer DeepSeek buy.

Community Sentiment

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CompareLLM Matrix

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LIVE

openrouter

Auto Router (Beta)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$-1,000,000/1M

DeepSeek

DeepSeek V4 Pro

Elo 1,536

LiveBench70.1%

SWE-bench71.6%

Speed70 tok/s

Output cost$3.96/1M

Frequently Asked Questions

Which is better overall, Auto Router (Beta) or DeepSeek V4 Pro?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Auto Router (Beta) or DeepSeek V4 Pro?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: Auto Router (Beta) output tokens are $-1,000,000/1M versus $3.96/1M. Input prices and retry rates still move the real bill.
Which is faster, Auto Router (Beta) or DeepSeek V4 Pro?: We do not have TTFT for both models.
Which has the larger context window?: Auto Router (Beta) accepts 2M tokens versus 1M.
Can I self-host either model?: DeepSeek V4 Pro is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Auto Router (Beta) and DeepSeek V4 Pro Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Auto Router (Beta) matchups →|All DeepSeek V4 Pro matchups →

DeepSeek V4 Pro vs DeepSeek R1 (previous deepseek)DeepSeek V4 Pro vs DeepSeek V4 Flash (next deepseek)DeepSeek V3 vs DeepSeek V4 Pro DeepSeek Coder V2 vs DeepSeek V4 Pro Claude Opus 4.5 vs DeepSeek V4 Pro Claude Opus 4.6 vs DeepSeek V4 Pro

Auto Router (Beta) vs DeepSeek V4 Pro benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Auto Router (Beta) (3)vsDeepSeek V4 Pro (7)

Auto Router (Beta): 3W (30%)Overall: DeepSeek V4 ProDeepSeek V4 Pro: 7W (70%)

← Auto Router (Beta)DeepSeek V4 Pro →

DeepSeek V4 Pro (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,536

Coding Elo

—vs1,544

SWE-bench

—vs71.6%

LiveBench

—vs70.1%

GPQA Diamond

—vs84%

Auto Router (Beta): 0WDeepSeek V4 Pro: 5W

DeepSeek V4 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs70 tok/s

Time to first token

—vs410 ms

Auto Router (Beta): 0WDeepSeek V4 Pro: 2W

Auto Router (Beta) (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$-1,000,000/1Mvs$3.96/1M

Input price

$-1,000,000/1Mvs$1.32/1M

Context window

2Mvs1M

Auto Router (Beta): 3WDeepSeek V4 Pro: 0W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatAuto Router (Beta)

Lower output list price ($-1,000,000/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGAuto Router (Beta)

Larger window (2M).

Screenshots / visionDeepSeek V4 Pro

DeepSeek V4 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Auto Router (Beta)	Lower output list price ($-1,000,000/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Auto Router (Beta)	Larger window (2M).
Screenshots / vision	DeepSeek V4 Pro	DeepSeek V4 Pro is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Auto Router (Beta) or DeepSeek V4 Pro?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Auto Router (Beta) or DeepSeek V4 Pro?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Auto Router (Beta) output tokens are $-1,000,000/1M versus $3.96/1M. Input prices and retry rates still move the real bill.

Which is faster, Auto Router (Beta) or DeepSeek V4 Pro?

We do not have TTFT for both models.

Which has the larger context window?

Auto Router (Beta) accepts 2M tokens versus 1M.

Can I self-host either model?

DeepSeek V4 Pro is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Auto Router (Beta) and DeepSeek V4 Pro Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

Auto Router (Beta)

Full Benchmark Score Matrix

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek vs Claude: the cheap-versus-frontier question, remapped

DeepSeek V4 Pro: high reasoning density per dollar

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Auto Router (Beta)

DeepSeek V4 Pro

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

No shared data

No shared data

Auto Router (Beta)

Full Benchmark Score Matrix

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

DeepSeek vs Claude: the cheap-versus-frontier question, remapped

DeepSeek V4 Pro: high reasoning density per dollar

DeepSeek R1 stays as the open-weights RL baseline

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Auto Router (Beta)

DeepSeek V4 Pro

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons