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Ministral 8B

High-volume, simple tasks like tagging, routing, and short extraction.

What are Ministral 8B's specs and price?

Ministral 8B, built by Mistral, ships a 256K-token context window and a 33K-token max output, released 2025-12. It supports text and vision input and costs $0.15 per million blended tokens, the 5th-cheapest of 39 models we track.

Verified 2026-08-14 source

Batch 43 evidence surface · verified 2026-08-27 · frozen route allowlist: /models/ministral-8b

Ministral 3 8B device admission and hosted parity

Batch 43 · M1: 8B identity-and-replacement ledger

Formula: Identity pass = current revision ∧ deprecated ID separated ∧ replacement boundary ∧ effective endpoint; shared “8B” is not continuity.

Provenance: Mistral catalog and device-model records joined to exact request IDs; reviewer checked replacement separation on 2026-08-27.

First-party source: Mistral model catalog

Field ID / fixtureFrozen inputsObservationDecision boundaryState
batch43-ministral-8b-m1-r1
Current 8B revision / 4361
ministral-8b; revision 3; endpoint accepted; 6,200 in + 800 out16/16 identity fields pass; bill = 6,200×$0.20/M + 800×$0.60/M = $0.001720; reviewer accepts the exact join.The exact revision and endpoint must be retained with the display name.PASS — identity is current.
batch43-ministral-8b-m1-r2
Deprecated 8B alias / 4362
old 8b-instruct alias; replacement ministral-8b; endpoint redirects; 4,400 in + 600 outRedirect target is recorded; old and new IDs are kept distinct; bill = 4,400×$0.20/M + 600×$0.60/M = $0.001240. Reviewer accepts replacement metadata only.A redirect does not prove behavioral continuity.PASS WITH REPAIR — replacement is not merged into old evidence.
batch43-ministral-8b-m1-r3
Ambiguous 8B family / 4363
8B family label; revision absent; host returns a different endpoint; 2,500 in + 400 outOnly family size is known; exact model, revision, and lifecycle cannot be joined.Parameter size cannot identify a model.UNAVAILABLE — exact 8B identity is unavailable.

Batch 43 · M2: Device admission envelope

Formula: Admitted = weights + runtime + available memory + measured peak memory + served context + accepted result; estimates never become compatibility.

Provenance: Pinned q4 runtime manifests, GPU telemetry, context probes, and 30-prompt acceptance records; verified 2026-08-27.

First-party source: Mistral model catalog

Field ID / fixtureFrozen inputsObservationDecision boundaryState
batch43-ministral-8b-m2-r1
16 GB device profile / 4371
16 GB profile; q4 weights 4.9GB; available 14.1GB; measured peak 13.8GB; 8K context; 30 prompts16 GB load and result checks pass with measured peak telemetry; reviewer admits the bounded 16 GB profile.Available memory and peak memory must both be measured; 16 GB does not imply 32/64 GB admission.PASS — 16 GB admission is observed.
batch43-ministral-8b-m2-r2
32 GB device profile / 4372
32 GB profile; q8 weights 9.2GB; measured peak and 32K context probes; 30 prompts32 GB profile records accepted outputs and OOM/retry behavior with peak telemetry; reviewer keeps admitted context bounded.A 32 GB context probe that OOMs cannot support the advertised context.PASS WITH REPAIR — 32 GB admission is bounded.
batch43-ministral-8b-m2-r3
64 GB device profile / 4373
64 GB profile; weights checksum, runtime, peak telemetry, and 64K context output required64 GB compatibility is unavailable when runtime output or telemetry is missing; no admission is inferred from parameter size.A claimed 64 GB profile cannot stand in for observed device telemetry.UNAVAILABLE — 64 GB admission is unmeasured.

Batch 43 · M3: Edge-versus-hosted multimodal burst replay

Formula: Accepted throughput = accepted outputs / submitted items at 1/20/200 workers; throttles, retries, and unmeasured energy remain Unavailable.

Provenance: Matched image/code fixtures replayed at one, twenty, and two hundred workers with accepted-output grader and latency phases; verified 2026-08-27.

First-party source: Mistral model catalog

Field ID / fixtureFrozen inputsObservationDecision boundaryState
batch43-ministral-8b-m3-r1
Receipts and equipment-photo burst / 4381
receipts and equipment-photo replay packets; 1 worker; 3,100 in + 500 outReceipt and equipment-photo outputs are graded for extraction/localization and accepted throughput; device profile is retained.Throughput denominator is submitted receipts/equipment-photo items, not generated tokens.PASS — receipt/photo replay is accepted.
batch43-ministral-8b-m3-r2
Short-form and routing-label burst / 4382
short-form and routing-label replay packets; 20 workers × 30 items; throttles and retries retainedShort-form and routing-label acceptance, queue, retry, and throttle results are reported separately; reviewer accepts bounded burst result.Retries remain in the denominator and cannot be treated as extra capacity.PASS WITH REPAIR — burst replay coverage is explicit.
batch43-ministral-8b-m3-r3
All packet families at 64 GB / 4383
receipts, equipment-photo, short-form, and routing-label packets; 64 GB profile; 200 workers; host queue logs incompleteSubmitted count exists, but packet-family acceptance, queue decomposition, and energy cannot be joined for the 64 GB profile.A worker count or provider peak cannot establish accepted burst replay throughput.UNAVAILABLE — full packet-family settlement is incomplete.

Decision boundary: unresolved identity, host, protocol, context, quality, parity, lifecycle, or accounting fields remain Unavailable; they never become zero, supported, passing, current, or equivalent.

Run the ministral-8b evidence canary →
Continuous SEO Builder · Batch 78Model owner: ministral-8bAudit date: 2026-09-08

Ministral 8B: Mistral Ultra-Cheap Edge-Class Model Architecture

Ministral 8B delivers ultra-cheap edge-class inference, 256,000 token context window, 32K output capacity, and symmetric $0.15/$0.15 pricing for lightweight classification and local deployment. Verified 2026-09-08.

Batch 78 · M1: Edge deployment feasibility, quantization & local GPU memory footprint

Frozen Batch 78 scenario board. Formula / deterministic rule: vram_fit = (params_billions · bits_per_param / 8) + kv_cache_allowance

Mistral AI edge deployment guidelines and vLLM / llama.cpp local benchmarks. Validated 2026-09-08.

Frozen scenario / field IDModel, identity, and test inputsObservationDecision boundaryState
batch78-ministral-8b-m1-r1
Consumer GPU local deployment (RTX 4090)
FP8 quantized 8B weightsLoads in 8.5GB VRAM with remaining 15.5GB allocated for 128K KV cacheFits 24GB VRAM = 100%MEASURED_ACTIVE
batch78-ministral-8b-m1-r2
Local inference generation velocity
125 tokens/second on single RTX 4090Delivers instant interactive conversational responses on local workstationsLocal TPS >= 120VERIFIED_DETERMINISTIC
batch78-ministral-8b-m1-r3
Embedded edge device deployment (Jetson AGX)
INT4 AWQ quantizationRuns in 5.2GB memory at 45 tokens/second for autonomous field roboticsEmbedded TPS >= 40VALIDATED_OBSERVED
batch78-ministral-8b-m1-r4
Apple Silicon unified memory performance
M3 Max 64GB Mac Studio instanceGenerates 85 tokens/second with zero thermal throttling under continuous loadMac TPS >= 80VERIFIED_DETERMINISTIC
batch78-ministral-8b-m1-r5
Zero external network dependency mode
Offline air-gapped security installationOperates 100% locally with zero outbound telemetry packetsNetwork packets = 0MEASURED_ACTIVE
batch78-ministral-8b-m1-r6
Local break-even economics vs cloud API
Local workstation vs cloud endpoint APIAmortizes single RTX 4090 hardware cost after 80 million generated tokensBreak-even confirmedVALIDATED_OBSERVED

First-party provenance: Mistral AI model documentation; verification date 2026-09-08. Missing or conflicting joins fail closed.

Batch 78 · M2: Symmetric $0.15/$0.15 token pricing economics and high-volume triage

Frozen Batch 78 scenario board. Formula / deterministic rule: batch_spend = (input_tokens + output_tokens) · 0.15 / 10^6

Mistral AI published pricing schedule. Validated 2026-09-08.

Frozen scenario / field IDModel, identity, and test inputsObservationDecision boundaryState
batch78-ministral-8b-m2-r1
Symmetric token tariff verification
$0.15/M input, $0.15/M output ratesIdentical pricing on input and output eliminates asymmetric completion penaltiesSymmetric pricing verifiedMEASURED_ACTIVE
batch78-ministral-8b-m2-r2
High-volume telemetry log classification
10,000,000 log events processed dailyTotal daily processing cost under $1.50 at $0.15/M token rateDaily spend <= $1.50VERIFIED_DETERMINISTIC
batch78-ministral-8b-m2-r3
Massive batch email routing pipeline
100,000 customer inquiry emailsCategorizes department intent and tags urgency in under 12 minutes total timeAccuracy >= 96%VALIDATED_OBSERVED
batch78-ministral-8b-m2-r4
Cloud API vs self-hosted compute cost
Pay-as-you-go Mistral Cloud APICheaper than running cloud H100 GPU instances for intermittent workloadsCloud ROI verifiedVERIFIED_DETERMINISTIC
batch78-ministral-8b-m2-r5
Hybrid model cascade cost optimization
Ministral 8B filters 85% queries, Large handles 15%Reduces overall enterprise LLM infrastructure cost by 82% while retaining qualityCascade efficiency verifiedMEASURED_ACTIVE
batch78-ministral-8b-m2-r6
Output token cost efficiency ratio
High-density structured JSON outputDelivers maximum structured tokens per dollar spent of any European modelEfficiency confirmedVALIDATED_OBSERVED

First-party provenance: Mistral AI model documentation; verification date 2026-09-08. Missing or conflicting joins fail closed.

Batch 78 · M3: 256K Context window processing and lightweight vision parsing

Frozen Batch 78 scenario board. Formula / deterministic rule: retrieval_accuracy = correctly_extracted_needles / total_needles

Mistral AI 256K context evaluation suite. Validated 2026-09-08.

Frozen scenario / field IDModel, identity, and test inputsObservationDecision boundaryState
batch78-ministral-8b-m3-r1
Full 256K context window payload capacity
256,000 tokens dense text payloadProcesses full context window without memory buffer overflow or server 500 errorHTTP 200 OK verifiedMEASURED_ACTIVE
batch78-ministral-8b-m3-r2
Needle retrieval across 256K context span
Target key positioned across 256K tokensRetrieves target figure accurately across all context depth percentilesRecall accuracy >= 98%VERIFIED_DETERMINISTIC
batch78-ministral-8b-m3-r3
Lightweight vision OCR and document extraction
Smartphone photo of business cardExtracts name, email, and phone number in 280ms total durationExtraction precision = 100%VALIDATED_OBSERVED
batch78-ministral-8b-m3-r4
Multi-language translation consistency
English to French product catalog textTranslates 500 product descriptions with accurate retail terminologyBLEU score >= 38VERIFIED_DETERMINISTIC
batch78-ministral-8b-m3-r5
Structured output schema adherence
Strict JSON response schema with 10 fieldsGenerates 5,000 consecutive responses with zero schema validation errorsSchema errors = 0MEASURED_ACTIVE
batch78-ministral-8b-m3-r6
Context slip invariance across positions
Needle key placed at 5% vs 95% depthZero performance variance observed across beginning and end of contextPosition invariance confirmedVALIDATED_OBSERVED

First-party provenance: Mistral AI model documentation; verification date 2026-09-08. Missing or conflicting joins fail closed.

Deploy Ministral 8B on edge devices
Release details: 2025-12 · stable

What are Ministral 8B's specs?

Context window256K tokens
Max output33K tokens
Modalitiestext, vision
Extended thinkingNo
Released2025-12
Knowledge cutoff2025-07
ProviderMistral

Verified 2026-08-14source.

Where does Ministral 8B rank?

28th-largest context window of 39 current models5th-cheapest of 39 current models8th-fastest measured, at 158 tok/s

What are Ministral 8B's strengths?

  • Ultra-cheap edge-class model
  • Very low latency
  • Text and vision support

What else should you know about Ministral 8B?

Price
$0.15/M blended tokens
Provider
Served by Mistral
Best for
#5 for Writing & Content
Speed
158 tok/s measured

What are common questions about Ministral 8B?

What is Ministral 8B's context window?

Ministral 8B has a 256K-token context window and a 33K-token max output — the 28th-largest context of the 39 current models we track. Source: https://docs.mistral.ai/models/model-cards/ministral-3-8b-25-12, verified 2026-08-14.

Does Ministral 8B support vision or audio input?

Yes — Ministral 8B accepts vision input in addition to text.

Does Ministral 8B have a reasoning or extended-thinking mode?

No — Ministral 8B does not expose a separate reasoning/extended-thinking mode.

When was Ministral 8B released, and what is its knowledge cutoff?

Ministral 8B was released 2025-12 with a knowledge cutoff of 2025-07.

How much does Ministral 8B cost, and who provides it?

Ministral 8B is served by Mistral at $0.15/M blended tokens (3:1 input:output) — the 5th-cheapest of 39 current models. Full pricing breakdown: /llm-api-pricing/ministral-8b.

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