Model comparison

DeepSeek-V3.1-Terminus vs Qwen3.7 Flash

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 39.5 on the Noometry Index. Qwen3.7 Flash costs 8.6× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.

Last verified October 10, 2026. 0 shared benchmarks.

DeepSeek-V3.1-Terminus

DeepSeek

42.6

Rank #96 Confirmed

Qwen3.7 Flash

Alibaba (Qwen)

39.5

Rank #152 Confirmed

Summary

Qwen3.7 Flash is cheaper at $0.03 / $0.13 per million input/output tokens, against $0.30 / $1 for DeepSeek-V3.1-Terminus.
Qwen3.7 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 Qwen3.7 Flash specifications
	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
Provider	DeepSeek	Alibaba (Qwen)
Noometry Index	42.6	39.5
Released	2025-09-22	2026-07-15
Weights	Open	Proprietary
Context window	164K	1M
Max output	66K	131K
Input $ / M tokens	$0.30	$0.03
Output $ / M tokens	$1	$0.13
Results tracked	16	7

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

Category by category

Coding Not comparable

DeepSeek-V3.1-Terminus: 41.5 (#114), Qwen3.7 Flash: —

Coding benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
SciCode	40.6%	—
LMArena Coding	1426	—
ALE-Bench	745.17	—

Reasoning Qwen3.7 Flash leads

DeepSeek-V3.1-Terminus: 25.7 (#126), Qwen3.7 Flash: 27.3 (#108)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
Kagi LLM Benchmark	57.4%	—
NYT Connections (extended)	—	43.8%
CritPt	1.7%	—
Chess Puzzles	—	23%
LMArena Hard Prompts	1427	—
Mystery Game Puzzles	—	15%
DTBench	81.3%	—
LMCA	28.6%	—
Epoch Capabilities Index	—	144.62

Math Qwen3.7 Flash leads

DeepSeek-V3.1-Terminus: 35.7 (#138), Qwen3.7 Flash: 37.3 (#100)

Math benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
FrontierMath (Tiers 1-3)	—	19.3%
OTIS Mock AIME 2024-2025	—	86.7%
LMArena Math	1402	—

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, Qwen3.7 Flash: 48.9 (#69)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
GPQA Diamond	—	82.3%

Multilingual Not comparable

DeepSeek-V3.1-Terminus: 52.3 (#87), Qwen3.7 Flash: —

Multilingual benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
LMArena Non-English	1407	—
LMArena Russian	1434	—

Instruction Following Not comparable

DeepSeek-V3.1-Terminus: 74.4 (#96), Qwen3.7 Flash: —

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
LMArena Instruction Following	1406	—

Long Context Not comparable

DeepSeek-V3.1-Terminus: 43.5 (#88), Qwen3.7 Flash: —

Long Context benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
LMArena Longer Query	1426	—

Writing & Preference Not comparable

DeepSeek-V3.1-Terminus: 61.3 (#87), Qwen3.7 Flash: —

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Qwen3.7 Flash
LMArena Text	1420	—
LMArena Creative Writing	1404	—
LMArena Multi-Turn	1411	—

Frequently asked questions

Is DeepSeek-V3.1-Terminus better than Qwen3.7 Flash?

Which is cheaper, DeepSeek-V3.1-Terminus or Qwen3.7 Flash?

Qwen3.7 Flash is cheaper. It lists at $0.03 per million input tokens and $0.13 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.30 and $1.

Which has the bigger context window?

Qwen3.7 Flash does, with 1M tokens against 164K.

How many benchmarks do DeepSeek-V3.1-Terminus and Qwen3.7 Flash share?

0 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Qwen3.7 Flash has 7.