Model comparison

DeepSeek-V3.1-Terminus vs Qwen3.6 Flash

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 38.8 on the Noometry Index.

Last verified October 10, 2026. 3 shared benchmarks.

DeepSeek-V3.1-Terminus

DeepSeek

43.1

Rank #97 Confirmed

Qwen3.6 Flash

Alibaba (Qwen)

38.8

Rank #182 Confirmed

Summary

They share 3 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 0 categories and Qwen3.6 Flash in 2 categories; one gap is clear of the uncertainty.
Qwen3.6 Flash is cheaper at $0.19 / $1.13 per million input/output tokens, against $0.27 / $1 for DeepSeek-V3.1-Terminus.
Qwen3.6 Flash accepts more context: 1M tokens versus 164K.
DeepSeek-V3.1-Terminus has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1-Terminus and Qwen3.6 Flash specifications
	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
Provider	DeepSeek	Alibaba (Qwen)
Noometry Index	43.1	38.8
Released	2025-09-22	2026-04-27
Weights	Open	Proprietary
Context window	164K	1M
Max output	147K	66K
Input $ / M tokens	$0.27	$0.19
Output $ / M tokens	$1	$1.13
Results tracked	16	13

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Category by category

Coding Not comparable

DeepSeek-V3.1-Terminus: 42.0 (#113), Qwen3.6 Flash: —

Coding benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
ALE-Bench	745.17	326.4
SciCode	40.6%	—
LMArena Coding	1426	—

Reasoning Qwen3.6 Flash leads

DeepSeek-V3.1-Terminus: 26.4 (#133), Qwen3.6 Flash: 29.0 (#96)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
DTBench	81.3%	77.1%
LMCA	28.6%	31%
SimpleBench	—	35.2%
Kagi LLM Benchmark	57.4%	—
CritPt	1.7%	—
Chess Puzzles	—	20%
LMArena Hard Prompts	1426	—
Mystery Game Puzzles	—	18%
Epoch Capabilities Index	—	143.26

Math Too close to call

DeepSeek-V3.1-Terminus: 38.5 (#137), Qwen3.6 Flash: 39.0 (#117)

Math benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
FrontierMath (Tiers 1-3)	—	22.5%
OTIS Mock AIME 2024-2025	—	84.4%
LMArena Math	1402	—
FrontierMath (Feb 2025 set)	—	10.3%
FrontierMath Tier 4 (v1)	—	0%

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, Qwen3.6 Flash: 42.1 (#100)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
GPQA Diamond	—	83.3%
SimpleQA Verified	—	15.9%

Multilingual Not comparable

DeepSeek-V3.1-Terminus: 52.1 (#92), Qwen3.6 Flash: —

Multilingual benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
LMArena Non-English	1407	—
LMArena Russian	1436	—

Instruction Following Not comparable

DeepSeek-V3.1-Terminus: 74.0 (#106), Qwen3.6 Flash: —

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
LMArena Instruction Following	1404	—

Long Context Not comparable

DeepSeek-V3.1-Terminus: 43.4 (#97), Qwen3.6 Flash: —

Long Context benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
LMArena Longer Query	1421	—

Writing & Preference Not comparable

DeepSeek-V3.1-Terminus: 61.0 (#92), Qwen3.6 Flash: —

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.6 Flash
LMArena Text	1419	—
LMArena Creative Writing	1403	—
LMArena Multi-Turn	1411	—

Frequently asked questions

Is DeepSeek-V3.1-Terminus better than Qwen3.6 Flash?

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 43.1 to 38.8 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1-Terminus or Qwen3.6 Flash?

Qwen3.6 Flash is cheaper. It lists at $0.19 per million input tokens and $1.13 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.27 and $1.

Which has the bigger context window?

Qwen3.6 Flash does, with 1M tokens against 164K.

How many benchmarks do DeepSeek-V3.1-Terminus and Qwen3.6 Flash share?

3 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Qwen3.6 Flash has 13.