Qwen3.7 Plus vs ReMM SLERP 13B
ReMM SLERP 13B costs 2.0x less per output token than Qwen3.7 Plus ($0.65 vs $1.28 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 33.2
- Overall
- 54.0
- Output $/M
- $1.28
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.65
Qwen3.7 Plus or ReMM SLERP 13B: which to pick
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; ReMM SLERP 13B has none, so the two cannot be ranked on coding.
Pick ReMM SLERP 13B for output tokens 2.0x cheaper ($0.65 vs $1.28 per million).
No benchmark has tested both yet. Qwen3.7 Plus has results on AA Coding Index, Vibe Code Bench (Vals AI) and Code migration (Vals AI); ReMM SLERP 13B has none yet. 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Qwen3.7 Plus has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.7 Plus has a AA Intelligence Index result, 25.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Plus has a AA Agentic Index result, 17.5.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.7 Plus has a Design Arena: websites result, 1269.
Directional only
Long documents
Listed context window
Qwen3.7 Plus
Qwen3.7 Plus takes 1M tokens against 6K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
ReMM SLERP 13B
Qwen3.7 Plus $0.0010, ReMM SLERP 13B $0.0007 per turn.
List prices
At a glance
- Coding index
- Qwen3.7 Plus 33.2 from 2 benchmarks, ReMM SLERP 13B 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
- Qwen3.7 Plus $1.28 against ReMM SLERP 13B $0.65 per million output tokens, 2.0x apart.
- Context window
- Qwen3.7 Plus takes 1M tokens, ReMM SLERP 13B 6K.
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 Index10 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| AA Coding Index | 55.9 | Not measured | Only Qwen3.7 Plus measured |
| Vibe Code Bench (Vals AI) | 46.4% | Not measured | Only Qwen3.7 Plus measured |
| Code migration (Vals AI) | 12.9% | Not measured | Only Qwen3.7 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | 52.8% | Not measured | Only Qwen3.7 Plus measured |
| SkillsBench (Vals AI) | 54.3% | Not measured | Only Qwen3.7 Plus measured |
| SciCode | 46.1% | Not measured | Only Qwen3.7 Plus measured |
| Terminal-Bench Hard (Artificial Analysis run) | 47.0% | Not measured | Only Qwen3.7 Plus measured |
| FrontierCode | 10.2% | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: coding | 1473 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: software and IT | 1473 | Not measured | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 33 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| AA Intelligence Index | 25.2 | Not measured | Only Qwen3.7 Plus measured |
| Epoch Capabilities Index | 147.0 | Not measured | Only Qwen3.7 Plus measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| AA Agentic Index | 17.5 | Not measured | Only Qwen3.7 Plus measured |
| Finance Agent (Vals AI) | 38.2% | Not measured | Only Qwen3.7 Plus measured |
| Tax Agent Bench (Vals AI) | 10.5% | Not measured | Only Qwen3.7 Plus measured |
| Legal Research Bench (Vals AI) | 16.4% | Not measured | Only Qwen3.7 Plus measured |
| Excel Modeling Benchmark (Vals AI) | 49.3% | Not measured | Only Qwen3.7 Plus measured |
| τ²-Bench Telecom | 93.0% | Not measured | Only Qwen3.7 Plus measured |
| OSWorld 2.0 | 2.8% | Not measured | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 90.0% | Not measured | Only Qwen3.7 Plus measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.6% | Not measured | Only Qwen3.7 Plus measured |
| GPQA Diamond (Epoch AI run) | 87.9% | Not measured | Only Qwen3.7 Plus measured |
| Mystery game puzzles | 17.0% | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts | 1460 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: expert | 1466 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts in English | 1460 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision: diagrams | 1292 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision: homework | 1295 | Not measured | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 93.3% | Not measured | Only Qwen3.7 Plus measured |
| FrontierMath, tiers 1 to 3 | 34.4% | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: math | 1467 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: mathematical work | 1470 | Not measured | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| MortgageTax (Vals AI) | 66.2% | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: science | 1464 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: medicine and healthcare | 1464 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: legal and government | 1451 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: business and finance | 1435 | Not measured | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| Design Arena: websites | 1269 | Not measured | Only Qwen3.7 Plus measured |
| Design Arena: UI components | 1258 | Not measured | Only Qwen3.7 Plus measured |
| Design Arena: game dev | 1262 | Not measured | Only Qwen3.7 Plus measured |
| Design Arena: data viz | 1277 | Not measured | Only Qwen3.7 Plus measured |
| Design Arena: 3D | 1238 | Not measured | Only Qwen3.7 Plus measured |
| Design Arena: all code categories | 1268 | Not measured | Only Qwen3.7 Plus measured |
| Design Arena: SVG | 1207 | Not measured | Only Qwen3.7 Plus measured |
| Design Arena: ASCII art | 1143 | Not measured | Only 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 index30 boards measured
| Benchmark | Qwen3.7 Plus | ReMM SLERP 13B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 39.3% | Not measured | Only Qwen3.7 Plus measured |
| Vals Multimodal Index | 53.9% | Not measured | Only Qwen3.7 Plus measured |
| IFBench | 78.0% | Not measured | Only Qwen3.7 Plus measured |
| Long context reasoning (AA-LCR) | 73.0% | Not measured | Only Qwen3.7 Plus measured |
| DTBench | 84.0% | Not measured | Only Qwen3.7 Plus measured |
| LMCA | 37.6% | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text | 1454 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: instruction following | 1439 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: creative writing | 1438 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision | 1278 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: English | 1458 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: non-English | 1445 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: Chinese | 1509 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: German | 1471 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: Japanese | 1412 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: Korean | 1413 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: French | 1472 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: Spanish | 1457 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: Russian | 1457 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: Polish | 1449 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: multi-turn | 1459 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: longer queries | 1454 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: writing and language | 1437 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Text: entertainment and media | 1422 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision: English | 1280 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision: Chinese | 1332 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision: reading text | 1288 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision: humor | 1261 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Vision: creative writing | 1258 | Not measured | Only Qwen3.7 Plus measured |
| LMArena Document | 1444 | Not measured | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 18 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
ReMM SLERP 13B costs less
Repository review
50K input + 3K output tokens
ReMM SLERP 13B costs less
Agent loop
200K input + 10K output tokens
ReMM SLERP 13B 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.
| Specification | Qwen3.7 Plus | ReMM SLERP 13B |
|---|---|---|
| Maker | Qwen | Undi95 |
| Weights | No public weights listed | Open weights |
| Released | June 3, 2026 | July 22, 2023 |
| Context window | 1M | 6K |
| Input $/Mtok | $0.32 | $0.35 |
| Output $/Mtok | $1.28 | $0.65 |
| Coding index | 33.2 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.7 Plus better than ReMM SLERP 13B for coding?
Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; ReMM SLERP 13B has none, so the two cannot be ranked on coding. Pick ReMM SLERP 13B for output tokens 2.0x cheaper ($0.65 vs $1.28 per million).
Which is cheaper, Qwen3.7 Plus or ReMM SLERP 13B?
Qwen3.7 Plus costs $0.32 per million input tokens and $1.28 per million output tokens; ReMM SLERP 13B costs $0.35 and $0.65. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3.7 Plus or ReMM SLERP 13B?
Qwen3.7 Plus, with 1M tokens against 6K.
Has any benchmark tested both Qwen3.7 Plus and ReMM SLERP 13B?
No benchmark has tested both yet. Qwen3.7 Plus has results on AA Coding Index, Vibe Code Bench (Vals AI) and Code migration (Vals AI); ReMM SLERP 13B has none yet. Compare them on price and context instead. Data as of October 22, 2026.