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Command R (08-2024) vs Qwen3 14B

Qwen3 14B costs 2.6x less per output token than Command R (08-2024) ($0.23 vs $0.60 per million). Updated October 21, 2026; no benchmark has tested both models yet.

Command R (08-2024)Cohere
Coding
No data
Overall
No data
Output $/M
$0.60
Qwen3 14BQwen
Coding
No data
Overall
No data
Output $/M
$0.23
vs $0.60 vs $0.23 per 1M output tokens. Qwen3 14B is 2.6x cheaper.

Command R (08-2024) or Qwen3 14B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Command R (08-2024) for a larger context window (128K against 41K tokens).

No benchmark has tested both yet. Command R (08-2024) has results on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts; Qwen3 14B on LiveCodeBench (Artificial Analysis run), SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Command R (08-2024) not benchmarked, Qwen3 14B not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
Command R (08-2024) $0.60 against Qwen3 14B $0.23 per million output tokens, 2.6x apart.
Context window
Command R (08-2024) takes 128K tokens, Qwen3 14B 41K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards measured
Coding benchmarks for Command R (08-2024) and Qwen3 14B
BenchmarkCommand R (08-2024)Qwen3 14BLeader
LiveCodeBench (Artificial Analysis run)Not measured52.3%Only Qwen3 14B measured
SciCodeNot measured30.7%Only Qwen3 14B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured5.3%Only Qwen3 14B measured
LMArena Text: coding1187Not measuredOnly Command R (08-2024) measured
LMArena Text: software and IT1197Not measuredOnly Command R (08-2024) measured
Neither model has a result on the other 34 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for Command R (08-2024) and Qwen3 14B
BenchmarkCommand R (08-2024)Qwen3 14BLeader
AA Intelligence IndexNot measured6.7Only Qwen3 14B measured
Epoch Capabilities IndexNot measured138.2Only Qwen3 14B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Agentic work benchmarks for Command R (08-2024) and Qwen3 14B
BenchmarkCommand R (08-2024)Qwen3 14BLeader
τ²-Bench TelecomNot measured34.5%Only Qwen3 14B measured
Berkeley Function Calling Leaderboard (BFCL)Not measured41.0%Only Qwen3 14B measured
Neither model has a result on the other 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
Reasoning benchmarks for Command R (08-2024) and Qwen3 14B
BenchmarkCommand R (08-2024)Qwen3 14BLeader
GPQA Diamond (Artificial Analysis run)Not measured60.4%Only Qwen3 14B measured
Humanity's Last Exam (Artificial Analysis run)Not measured4.5%Only Qwen3 14B measured
GPQA Diamond (Epoch AI run)Not measured63.8%Only Qwen3 14B measured
LMArena Text: hard prompts1186Not measuredOnly Command R (08-2024) measured
LMArena Text: expert1173Not measuredOnly Command R (08-2024) measured
LMArena Text: hard prompts in English1194Not measuredOnly Command R (08-2024) measured
Kagi LLM BenchmarkNot measured49.1%Only Qwen3 14B measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Math benchmarks for Command R (08-2024) and Qwen3 14B
BenchmarkCommand R (08-2024)Qwen3 14BLeader
AA Math IndexNot measured58.0Only Qwen3 14B measured
AIME 2025 (Artificial Analysis run)Not measured58.0%Only Qwen3 14B measured
OTIS Mock AIMENot measured66.4%Only Qwen3 14B measured
LMArena Text: math1188Not measuredOnly Command R (08-2024) measured
LMArena Text: mathematical work1198Not measuredOnly Command R (08-2024) measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Knowledge benchmarks for Command R (08-2024) and Qwen3 14B
BenchmarkCommand R (08-2024)Qwen3 14BLeader
MMLU Pro (Artificial Analysis run)Not measured77.4%Only Qwen3 14B measured
LMArena Text: science1252Not measuredOnly Command R (08-2024) measured
LMArena Text: medicine and healthcare1238Not measuredOnly Command R (08-2024) measured
LMArena Text: legal and government1268Not measuredOnly Command R (08-2024) measured
LMArena Text: business and finance1215Not measuredOnly Command R (08-2024) measured
Neither model has a result on the other 13 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards measured
General benchmarks for Command R (08-2024) and Qwen3 14B
BenchmarkCommand R (08-2024)Qwen3 14BLeader
IFBenchNot measured40.5%Only Qwen3 14B measured
Long context reasoning (AA-LCR)Not measured0.0%Only Qwen3 14B measured
DTBenchNot measured64.0%Only Qwen3 14B measured
LMCANot measured18.2%Only Qwen3 14B measured
Fiction.LiveBenchNot measured62.5%Only Qwen3 14B measured
LMArena Text1229Not measuredOnly Command R (08-2024) measured
LMArena Text: instruction following1197Not measuredOnly Command R (08-2024) measured
LMArena Text: creative writing1234Not measuredOnly Command R (08-2024) measured
LMArena Text: English1238Not measuredOnly Command R (08-2024) measured
LMArena Text: non-English1216Not measuredOnly Command R (08-2024) measured
LMArena Text: Chinese1227Not measuredOnly Command R (08-2024) measured
LMArena Text: German1216Not measuredOnly Command R (08-2024) measured
LMArena Text: Japanese1166Not measuredOnly Command R (08-2024) measured
LMArena Text: Korean1162Not measuredOnly Command R (08-2024) measured
LMArena Text: Russian1227Not measuredOnly Command R (08-2024) measured
LMArena Text: multi-turn1213Not measuredOnly Command R (08-2024) measured
LMArena Text: longer queries1230Not measuredOnly Command R (08-2024) measured
LMArena Text: writing and language1241Not measuredOnly Command R (08-2024) measured
LMArena Text: entertainment and media1223Not measuredOnly Command R (08-2024) measured
Neither model has a result on the other 27 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Command R (08-2024)$0.0004Fits in one request
Qwen3 14B$0.0002Fits in one request

Qwen3 14B costs less

Repository review

50K input + 3K output tokens

Command R (08-2024)$0.0093Fits in one request
Qwen3 14B$0.0062Exceeds the context window

Qwen3 14B costs less

Agent loop

200K input + 10K output tokens

Command R (08-2024)$0.036Exceeds the context window
Qwen3 14B$0.024Exceeds the context window

Qwen3 14B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Command R (08-2024) and Qwen3 14B
SpecificationCohere Command R (08-2024)Qwen3 14B
MakerCohereQwen
WeightsNo public weights listedOpen weights
ReleasedAugust 30, 2024April 28, 2025
Context window128K41K
Input $/Mtok$0.15$0.11
Output $/Mtok$0.60$0.23
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Command R (08-2024) better than Qwen3 14B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Command R (08-2024) for a larger context window (128K against 41K tokens).

Which is cheaper, Command R (08-2024) or Qwen3 14B?

Command R (08-2024) costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3 14B costs $0.11 and $0.23. Cost per solved task is known for neither of them.

Which has the bigger context window, Command R (08-2024) or Qwen3 14B?

Command R (08-2024), with 128K tokens against 41K.

Has any benchmark tested both Command R (08-2024) and Qwen3 14B?

No benchmark has tested both yet. Command R (08-2024) has results on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts; Qwen3 14B on LiveCodeBench (Artificial Analysis run), SciCode and Terminal-Bench Hard (Artificial Analysis run). Compare them on price and context instead. Data as of October 21, 2026.

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