Model profile
openrouter

Auto Router

Auto Router is a budget-priced multimodal generalist from openrouter with partial runtime data, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalN/A latencyLarge contextBudget pricing
Intelligence
N/A

Benchmark blend

Coding
N/A

Dev workflow signal

Context
2000K Tokens

Large

Input Price
$-1000000.00

Budget tier

Decision snapshot
93

Auto Router currently reads as a budget multimodal option with large context and a partially published runtime profile.

Overall profile
Flagship profile
Best for
Long-context research / Multimodal
Latency tier
N/A
Price tier
Budget
Source coverage
OpenRouterVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
N/A
N/A

General reasoning and benchmark headroom.

Unavailable
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
2000K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$-1000000.00
86

$-1000000.00 output / 1M

Efficient

Editorial Profile

Auto Router in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Flagship profileCoding score N/AMath score N/AVision enabled

Your prompt will be processed by a meta-model and routed to one of dozens of models (see below), optimizing for the best possible output. To see which model was used,...

Identity

openrouter multimodal profile

Positioning

Long-context research / Multimodal with large context and partially published runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

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Intelligence
N/A
Context
128K Tokens
Input Price
$-1000000.00
openrouter

Free Models Router

Intelligence
N/A
Context
200K Tokens
Input Price
$0.00

Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

No benchmark data is available for this model yet.

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
2000K Tokens
Vision
Enabled
Modalities
audio, file, image, text, video
Tokenizer
Router
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_completion_tokensmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_pweb_search_options
Input Modalities
audiofileimagetextvideo
Output Modalities
imagetext
Price architecture
Input
per 1M input tokens
$-1000000.00
Output
per 1M output tokens
$-1000000.00
Blended
AA 3:1 mix
N/A

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.