Model comparison

DeepSeek-R1 vs Magistral Medium

DeepSeek-R1 is the stronger model overall, scoring 42.3 to 35.2 on the Noometry Index.

Last verified October 11, 2026. 22 shared benchmarks.

DeepSeek-R1

DeepSeek

42.3

Rank #115 Confirmed

Magistral Medium

Mistral AI

35.2

Rank #227 Confirmed

Summary

They share 22 benchmarks with published results for both. DeepSeek-R1 scores higher in 8 categories and Magistral Medium in 0 categories; 8 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where DeepSeek-R1 leads 61.4 to 46.3.
The biggest single-benchmark swing is Kagi LLM Benchmark: 69.4% for DeepSeek-R1 and 16.2% for Magistral Medium.
DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $2 / $5 for Magistral Medium.
Magistral Medium accepts more context: 262K tokens versus 164K.
Magistral Medium has downloadable open weights; the other is API-only.

Side by side

DeepSeek-R1 and Magistral Medium specifications
	DeepSeek-R1	Magistral Medium
Provider	DeepSeek	Mistral AI
Noometry Index	42.3	35.2
Released	2025-01-20	2025-03-17
Weights	Proprietary	Open
Context window	164K	262K
Max output	64K	16K
Input $ / M tokens	$0.50	$2
Output $ / M tokens	$2.15	$5
Results tracked	52	22

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding DeepSeek-R1 leads

DeepSeek-R1: 46.3 (#68), Magistral Medium: 39.1 (#161)

Coding benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
SciCode	35.7%	39.2%
LMArena Coding	1427	1319
Aider Polyglot	71.4%	—
WeirdML	41.6%	—
LiveBench Coding	66.7%	—
ALE-Bench	804.12	—
AlgoTune	1.7	—

Agentic & Tool Use Not comparable

DeepSeek-R1: 30.7 (#75), Magistral Medium: —

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
DeepResearch Bench	35.1%	—
BALROG	34.9%	—
METR Time Horizons	53.8%	—

Reasoning DeepSeek-R1 leads

DeepSeek-R1: 18.6 (#278), Magistral Medium: 8.6 (#348)

Reasoning benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
ARC-AGI-2	1.3%	0%
Kagi LLM Benchmark	69.4%	16.2%
ARC-AGI-1	21.2%	6.1%
CritPt	1.1%	0.3%
LMArena Hard Prompts	1416	1267
SimpleBench	40.8%	—
LiveBench Reasoning	83.2%	—
LiveBench Data Analysis	69.8%	—
Epoch Capabilities Index	141.29	—
ForecastBench	60	—
LiveBench	71.6%	—

Math DeepSeek-R1 leads

DeepSeek-R1: 43.8 (#79), Magistral Medium: 35.1 (#189)

Math benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
LMArena Math	1400	1250
OTIS Mock AIME 2024-2025	66.4%	—
Omni-MATH	42.4%	—
LiveBench Math	80.7%	—
MATH Level 5	96.6%	—

Knowledge DeepSeek-R1 leads

DeepSeek-R1: 44.5 (#87), Magistral Medium: 33.5 (#202)

Knowledge benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
LMArena Expert	1394	1223
GPQA Diamond	76.3%	—
MMLU-Pro	79.3%	—
Confabulations	12.7%	—
Vectara Hallucination Rate	11.3%	—
GPQA (HELM)	66.6%	—

Multilingual DeepSeek-R1 leads

DeepSeek-R1: 52.4 (#85), Magistral Medium: 39.6 (#224)

Multilingual benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
LMArena Non-English	1412	1232
LMArena Chinese	1442	1227
LMArena French	1417	1267
LMArena German	1404	1248
LMArena Japanese	1391	1175
LMArena Korean	1360	1125
LMArena Russian	1423	1224
LMArena Spanish	1411	1271

Instruction Following DeepSeek-R1 leads

DeepSeek-R1: 72.0 (#143), Magistral Medium: 66.0 (#211)

Instruction Following benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
LMArena Instruction Following	1382	1254
LiveBench Instruction Following	80.5%	—
IFEval	78.4%	—

Long Context DeepSeek-R1 leads

DeepSeek-R1: 45.4 (#36), Magistral Medium: 39.3 (#183)

Long Context benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
LMArena Longer Query	1391	1295
Fiction.LiveBench	75%	—

Writing & Preference DeepSeek-R1 leads

DeepSeek-R1: 61.4 (#88), Magistral Medium: 46.3 (#219)

Writing & Preference benchmarks
Benchmark	DeepSeek-R1	Magistral Medium
LMArena Text	1428	1255
LMArena Creative Writing	1405	1245
LMArena Multi-Turn	1405	1275
Short-Story Creative Writing	83%	—
EQ-Bench Creative Writing	1500	—
WildBench	82.8%	—
LiveBench Language	48.5%	—

Frequently asked questions

Is DeepSeek-R1 better than Magistral Medium?

DeepSeek-R1 is the stronger model overall, scoring 42.3 to 35.2 on the Noometry Index.

Which is cheaper, DeepSeek-R1 or Magistral Medium?

DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Magistral Medium lists at $2 and $5.

Is DeepSeek-R1 or Magistral Medium better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 39.1 in the Noometry coding category.

Which has the bigger context window?

Magistral Medium does, with 262K tokens against 164K.

How many benchmarks do DeepSeek-R1 and Magistral Medium share?

22 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Magistral Medium has 22.