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Ember-1 vs Qwen3.7 Plus

Ember-1 leads Qwen3.7 Plus on coding, 52.6 to 33.2 on the Vibe Coding Index, and Qwen3.7 Plus costs 11.7x less per output token ($1.28 vs $15.00 per million). Updated October 21, 2026; 6 benchmarks have a result for both.

Ember-1Fireworks
Coding
52.6
Overall
No data
Output $/M
$15.00
6
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
0
vs boards won of 6 shared

Ember-1 or Qwen3.7 Plus: which to pick

Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus.

Pick Qwen3.7 Plus for output tokens 11.7x cheaper ($1.28 vs $15.00 per million).

Shared results
6
Ember-1 only
8
Qwen3.7 Plus only
69
Like-for-like categories
2 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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
Ember-1 52.6 from 2 benchmarks, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Coding, 28.6 points apart on average over 2 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Ember-1 83.9% against Qwen3.7 Plus 46.4%, 37.5 points apart on a 0 to 100 scale.
Output price
Ember-1 $15.00 against Qwen3.7 Plus $1.28 per million output tokens, 11.7x apart.
Context window
Ember-1 takes 1.05M tokens, Qwen3.7 Plus 1M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryEmber-1BarsQwen3.7 PlusTies
Coding20
Agentic work40
All shared boards60
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
AA Coding IndexNot measured55.9Only Qwen3.7 Plus measured
Terminal-Bench 4 (Vals AI)20.7%Not measuredOnly Ember-1 measured
Vibe Code Bench (Vals AI)83.9%46.4%Ember-1
Code migration (Vals AI)32.5%12.9%Ember-1
IOI (Vals AI)46.3%Not measuredOnly Ember-1 measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
CyberBench (Vals AI)69.5%Not measuredOnly Ember-1 measured
SciCodeNot measured46.1%Only Qwen3.7 Plus measured
Terminal-Bench Hard (Artificial Analysis run)Not measured47.0%Only Qwen3.7 Plus measured
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
LMArena Text: codingNot measured1473Only Qwen3.7 Plus measured
LMArena Text: software and ITNot measured1473Only Qwen3.7 Plus measured
Neither model has a result on the other 26 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
AA Intelligence IndexNot measured25.2Only Qwen3.7 Plus measured
Epoch Capabilities IndexNot measured147.0Only Qwen3.7 Plus measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
Agentic work benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
AA Agentic IndexNot measured17.5Only Qwen3.7 Plus measured
Finance Agent (Vals AI)51.8%38.2%Ember-1
Tax Agent Bench (Vals AI)31.1%10.5%Ember-1
Legal Research Bench (Vals AI)44.7%16.4%Ember-1
Excel Modeling Benchmark (Vals AI)63.4%49.3%Ember-1
BioMysteryBench (Vals AI)67.0%Not measuredOnly Ember-1 measured
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly Ember-1 measured
Vals Science Index31.8%Not measuredOnly Ember-1 measured
τ²-Bench TelecomNot measured93.0%Only Qwen3.7 Plus measured
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Neither model has a result on the other 31 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Reasoning benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
MysteryMechanism (Vals AI)22.5%Not measuredOnly Ember-1 measured
GPQA Diamond (Artificial Analysis run)Not measured90.0%Only Qwen3.7 Plus measured
Humanity's Last Exam (Artificial Analysis run)Not measured35.6%Only Qwen3.7 Plus measured
GPQA Diamond (Epoch AI run)Not measured87.9%Only Qwen3.7 Plus measured
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard promptsNot measured1460Only Qwen3.7 Plus measured
LMArena Text: expertNot measured1466Only Qwen3.7 Plus measured
LMArena Text: hard prompts in EnglishNot measured1460Only Qwen3.7 Plus measured
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
OTIS Mock AIMENot measured93.3%Only Qwen3.7 Plus measured
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
LMArena Text: mathNot measured1467Only Qwen3.7 Plus measured
LMArena Text: mathematical workNot measured1470Only Qwen3.7 Plus measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
LMArena Text: scienceNot measured1464Only Qwen3.7 Plus measured
LMArena Text: medicine and healthcareNot measured1464Only Qwen3.7 Plus measured
LMArena Text: legal and governmentNot measured1451Only Qwen3.7 Plus measured
LMArena Text: business and financeNot measured1435Only Qwen3.7 Plus measured
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
Design Arena: websitesNot measured1269Only Qwen3.7 Plus measured
Design Arena: UI componentsNot measured1261Only Qwen3.7 Plus measured
Design Arena: game devNot measured1262Only Qwen3.7 Plus measured
Design Arena: data vizNot measured1276Only Qwen3.7 Plus measured
Design Arena: 3DNot measured1239Only Qwen3.7 Plus measured
Design Arena: all code categoriesNot measured1269Only Qwen3.7 Plus measured
Design Arena: SVGNot measured1208Only Qwen3.7 Plus measured
Design Arena: ASCII artNot measured1143Only Qwen3.7 Plus measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index31 boards, none shared
General benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
Public Benefits Bench (Vals AI)66.2%Not measuredOnly Ember-1 measured
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBenchNot measured78.0%Only Qwen3.7 Plus measured
Long context reasoning (AA-LCR)Not measured73.0%Only Qwen3.7 Plus measured
DTBenchNot measured84.0%Only Qwen3.7 Plus measured
LMCANot measured37.6%Only Qwen3.7 Plus measured
LMArena TextNot measured1454Only Qwen3.7 Plus measured
LMArena Text: instruction followingNot measured1439Only Qwen3.7 Plus measured
LMArena Text: creative writingNot measured1438Only Qwen3.7 Plus measured
LMArena VisionNot measured1278Only Qwen3.7 Plus measured
LMArena Text: EnglishNot measured1458Only Qwen3.7 Plus measured
LMArena Text: non-EnglishNot measured1445Only Qwen3.7 Plus measured
LMArena Text: ChineseNot measured1509Only Qwen3.7 Plus measured
LMArena Text: GermanNot measured1471Only Qwen3.7 Plus measured
LMArena Text: JapaneseNot measured1412Only Qwen3.7 Plus measured
LMArena Text: KoreanNot measured1413Only Qwen3.7 Plus measured
LMArena Text: FrenchNot measured1472Only Qwen3.7 Plus measured
LMArena Text: SpanishNot measured1457Only Qwen3.7 Plus measured
LMArena Text: RussianNot measured1457Only Qwen3.7 Plus measured
LMArena Text: PolishNot measured1449Only Qwen3.7 Plus measured
LMArena Text: multi-turnNot measured1459Only Qwen3.7 Plus measured
LMArena Text: longer queriesNot measured1454Only Qwen3.7 Plus measured
LMArena Text: writing and languageNot measured1437Only Qwen3.7 Plus measured
LMArena Text: entertainment and mediaNot measured1422Only Qwen3.7 Plus measured
LMArena Vision: EnglishNot measured1280Only Qwen3.7 Plus measured
LMArena Vision: ChineseNot measured1332Only Qwen3.7 Plus measured
LMArena Vision: reading textNot measured1288Only Qwen3.7 Plus measured
LMArena Vision: humorNot measured1261Only Qwen3.7 Plus measured
LMArena Vision: creative writingNot measured1258Only Qwen3.7 Plus measured
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Ember-1 and Qwen3.7 Plus
BenchmarkEmber-1Qwen3.7 PlusLeader
Neither model has a result on 5 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

Ember-1$0.011Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

Qwen3.7 Plus costs less

Repository review

50K input + 3K output tokens

Ember-1$0.195Fits in one request
Qwen3.7 Plus$0.020Fits in one request

Qwen3.7 Plus costs less

Agent loop

200K input + 10K output tokens

Ember-1$0.750Fits in one request
Qwen3.7 Plus$0.077Fits in one request

Qwen3.7 Plus 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 Ember-1 and Qwen3.7 Plus
SpecificationFireworks Ember-1Qwen3.7 Plus
MakerFireworksQwen
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 24, 2026June 3, 2026
Context window1.05M1M
Input $/Mtok$3.00$0.32
Output $/Mtok$15.00$1.28
Coding index52.633.2
Independent measurements behind it22
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Ember-1 better than Qwen3.7 Plus for coding?

Pick Ember-1 for coding: it scores 52.6 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus. Pick Qwen3.7 Plus for output tokens 11.7x cheaper ($1.28 vs $15.00 per million).

Which is cheaper, Ember-1 or Qwen3.7 Plus?

Ember-1 costs $3.00 per million input tokens and $15.00 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.

Which has the bigger context window, Ember-1 or Qwen3.7 Plus?

Ember-1, with 1.05M tokens against 1M.

How many benchmarks is the Ember-1 vs Qwen3.7 Plus comparison based on?

6 benchmarks have a result for both models as of October 21, 2026. Ember-1's coding index rests on 2 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/fireworks-ember-1-vs-qwen3-7-plus" title="Ember-1 vs Qwen3.7 Plus, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/fireworks-ember-1-vs-qwen3-7-plus">LLMBenchmark.ai, Ember-1 vs Qwen3.7 Plus</a></p>