Model profile
Unknown

Sarvam M (Reasoning)

Sarvam M (Reasoning) is a budget text-first model from Unknown with a heavy runtime profile, unknown context posture, and the clearest fit around coding / agent workflows.

Best for: Coding / Agent workflowsHeavy latencyUnknown contextBudget pricing
Intelligence
8.4

Benchmark blend

Coding
0.295

Dev workflow signal

Context
N/A

Unknown

Input Price
$0.00

Budget tier

Decision snapshot
37

Sarvam M (Reasoning) currently reads as a budget text-first option with unknown context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Coding / Agent workflows
Latency tier
Heavy
Price tier
Budget
Source coverage
OpenRouter

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
8.4
8

General reasoning and benchmark headroom.

Limited
Speed
N/A
46

Latency data is partial.

Situational
Context
N/A
34

How much prompt and task state can stay in view.

Limited
Price
$0.00
86

$0.00 output / 1M

Efficient

Editorial Profile

Sarvam M (Reasoning) in one narrative

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

Use-case specificCoding score 40Math score 36

The Sarvam M (Reasoning) AI model by Unknown.

Identity

Unknown text-first profile

Positioning

Coding / Agent workflows with unknown context and heavy runtime.

Cost posture

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

Strengths
  • The available source data suggests a balanced profile rather than one dominant edge.

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

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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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.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
8.4
MMLU Pro
69.6%
GPQA
41.6%
Coding

Software implementation, debugging quality, and coding benchmark signal.

LiveCodeBench
0.295

Extra benchmark cuts are not available for this category 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
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$0.00
Output
per 1M output tokens
$0.00
Blended
AA 3:1 mix
N/A

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