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Is there an AI for this?

Model

Devstral 2 123B

Recorded as suitable for coding, agentic, reasoning.

Source
Model registry API
Verified
19 Sep 2026
Confidence
High

01What this is

Author
mistralai
Family
Devstral 2
Task
text-generation
Hugging Face
mistralai/Devstral-2-123B-Instruct-2512
OpenRouter
mistralai/devstral-2512
Also known as
Devstral 2, devstral-2-123b, devstral

02Registry facts

19 Sep 2026
LicenceFACT

other

FreshRetrieved 19 Sep 2026
ParametersFACT

125.0B

FreshRetrieved 19 Sep 2026
Context lengthFACT

not returned by the registry

Evidence not verified
Downloads (30 days)FACT

15,329

FreshRetrieved 19 Sep 2026
LikesFACT

340

FreshRetrieved 19 Sep 2026
GatedFACT

no

FreshRetrieved 19 Sep 2026

Model

downloadsFACT

15329

Verification may be outdatedRetrieved 19 Sep 2026
gatedFACT

false

Verification may be outdatedRetrieved 19 Sep 2026
hosted context length · MistralFACT

262144

Verification may be outdatedRetrieved 19 Sep 2026
likesFACT

340

Verification may be outdatedRetrieved 19 Sep 2026
model licenseFACT

other

Verification may be outdatedRetrieved 19 Sep 2026
parameter countFACT

125025989840

Verification may be outdatedRetrieved 19 Sep 2026

Pricing

hosted price completion per m · MistralFACT

2.0000

AgeingRetrieved 19 Sep 2026
hosted price prompt per m · MistralFACT

0.4000

AgeingRetrieved 19 Sep 2026

Other

available on platform · vendorFACT

vendor

Evidence not verified — the quoted phrase was not found in the fetched document.

Evidence not verified
available on platform · awsFACT

aws

The source document changed after this was recorded; it is queued for re-checking.

Verification may be outdatedRetrieved 19 Sep 2026
last modifiedFACT

2026-07-15T12:19:49.000Z

Verification may be outdatedRetrieved 19 Sep 2026
libraryFACT

vllm

AgeingRetrieved 19 Sep 2026

03VRAM by quantisation

ASSESSMENT

Peak VRAM for serving this model, computed by lib/deployment/hardware.ts from weights + KV cache + 15% runtime overhead. Inputs: 125.0B parameters, 8,192 tokens of context (assumed — none fetched yet), 4 concurrent requests (assumed).

Decimal GB (10⁹ bytes), matching how GPU memory is advertised.
QuantisationWeightsTotal
bf16bf16 is two bytes per weight, the same arithmetic as fp16.250.05 GB304.85 GB
fp8125.03 GB161.07 GB
int462.51 GB89.18 GB

What this estimate assumes

  • Weights: 125.0B parameters × 2 bytes per parameter (fp16) = 250.05 GB.
  • No model configuration was supplied, so the KV cache uses the size heuristic for this band: 0.459 MB per token, from extrapolated above 90B — no configuration was fetched for this band.
  • KV cache: 0.459 MB per token × 8,192 tokens of context × 4 concurrent requests = 15.03 GB, sized for every user holding a full context at once.
  • Overhead: 15% of weights plus KV cache for the runtime, activations and memory fragmentation = 39.76 GB.
  • GB means 10⁹ bytes, matching how GPU memory is advertised.
  • KV cache held at fp16 (2 bytes per element); quantising weights does not by itself quantise the cache.
  • Peak figure, not average: prefix caching and paged attention usually keep real usage lower, while speculative decoding, CUDA graphs and a second resident model push it higher.
  • "Concurrent" counts requests generated at the same instant, not people: 4 simultaneous requests is the worst case this estimate is built on — measure yours before buying.

04Hardware profiles

No hardware profile was sized for this answer.


05Hosted providers

Prompt (per million tokens, USD)FACT

0.39999999999999997

Source: openrouter

FreshRetrieved 19 Sep 2026
Completion (per million tokens, USD)FACT

2

FreshRetrieved 19 Sep 2026
ProviderContext
Mistral262,144

06Deployment stacks

0 using it

No published deployment stack names this model yet.


07Evidence

10 verified
  1. 01
    Tier 2official vendor legal documentationVendor legal and technical documentation

    Models at a glance - Amazon Bedrock

    https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards.html

    AgeingRetrieved 19 Sep 2026sha256:4c3b2b576226

    1 record

  2. 02–04
    Tier 4official repository / model cardOpenRouter

    OpenRouter endpoints — mistralai/devstral-2512

    https://openrouter.ai/api/v1/models/mistralai/devstral-2512/endpoints

    AgeingRetrieved 19 Sep 2026sha256:2ef4ec50068c

    3 records · ·

  3. 05–11
    Tier 4official repository / model cardHugging Face Hub

    Hugging Face model card data — mistralai/Devstral-2-123B-Instruct-2512

    https://huggingface.co/api/models/mistralai/Devstral-2-123B-Instruct-2512

    AgeingRetrieved 19 Sep 2026sha256:a1f1338707b0

    7 records · · · · · ·

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