SI Index Data as of Oct 9, 2026

Magistral Medium (latest): Price, Context, Benchmarks, and Release Details

mistral provisional listing · first seen Oct 8, 2026 · score computed Oct 9, 2026, 01:09 UTC
44.1
SI Score (method si-v3-retained-evidence-2)
16% confidence 16 percent, Low confidence — 1 of 7 expected sources in
Coverage 13% of expected source weight · 100% confidence at 80% coverage

Pillar breakdown

Coding (weight 40 percent) —
Math (weight 15 percent) —
Preference (weight 15 percent) —
Reasoning (weight 30 percent) 3.6

Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.

Facts

Input price / 1M
$1.50LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://docs.mistral.ai/models/model-cards/mistral-medium-3-5-26-04. Exact endpoint only; cache/batch/long-context rates excluded Retrieved Oct 9, 2026 · MIT
Open source ↗
Output price / 1M
$7.50LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://docs.mistral.ai/models/model-cards/mistral-medium-3-5-26-04. Exact endpoint only; cache/batch/long-context rates excluded Retrieved Oct 9, 2026 · MIT
Open source ↗
Context window
128Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
16.4Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
Mar 17, 2025models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Open weights
Nomodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
textmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

Benchmark results

8 results
Benchmark Raw result Normalized (0–100) Pillar
arc agi v1 public eval 8.9%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		8.9 reasoning
arc agi v1 public eval 8.0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506-thinkingPublished Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		8.0 reasoning
arc agi v1 semi private 5.9%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		5.9 reasoning
arc agi v1 semi private 6.1%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506-thinkingPublished Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		6.1 reasoning
arc agi v2 public eval 0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		0.0 reasoning
arc agi v2 public eval 0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506-thinkingPublished Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		0.0 reasoning
arc agi v2 semi private 0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506Published Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		0.0 reasoning
arc agi v2 semi private 0%ARC PrizeARC Prize steward-published result; exact edition/subset; publication time is HTTP Last-Modified of the aggregate export, not the evaluation date. [variant] magistral-medium-2506-thinkingPublished Oct 6, 2026 Retrieved Oct 9, 2026 · factual citation
Open source ↗ 		0.0 reasoning

Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.

Sources: in and pending

in Reported (1)

  • ARC Prize · arrived Oct 8, 2026

pending Awaiting (6)

  • Epoch AI Benchmarking · carries 25% of expected weight
  • Humanity’s Last Exam · carries 13% of expected weight
  • Official model cards via models.dev · carries 4% of expected weight
  • LiveBench · carries 13% of expected weight
  • LMArena / Arena · carries 25% of expected weight
  • Terminal-Bench · carries 6% of expected weight

The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.