Qwen3.5-Flash vs Relace Search
Qwen3.5-Flash costs 11.5x less per output token than Relace Search ($0.26 vs $3.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 41.1
- Overall
- 50.1
- Output $/M
- $0.26
- Coding
- No data
- Overall
- No data
- Output $/M
- $3.00
Qwen3.5-Flash or Relace Search: which to pick
Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Relace Search has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Qwen3.5-Flash has results on LMArena WebDev, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); Relace Search 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 Qwen3.5-Flash has a coding score, so no call is made.
One side not measured
Reasoning
GPQA Diamond
No call
Only Qwen3.5-Flash has a GPQA Diamond result, 82.8%.
Directional only
Math
AIME
No call
Only Qwen3.5-Flash has a AIME result, 92.5%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5-Flash has a MMLU Pro result, 84.1%.
Directional only
Long documents
Listed context window
Qwen3.5-Flash
Qwen3.5-Flash takes 1M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-Flash
Qwen3.5-Flash $0.0002, Relace Search $0.0025 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5-Flash has the number, $0.40.
Directional only
At a glance
- Coding index
- Qwen3.5-Flash 41.1 from 2 benchmarks, Relace Search 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
- Qwen3.5-Flash $0.26 against Relace Search $3.00 per million output tokens, 11.5x apart.
- Context window
- Qwen3.5-Flash takes 1M tokens, Relace Search 256K.
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 Index8 boards measured
| Benchmark | Qwen3.5-Flash | Relace Search | Leader |
|---|---|---|---|
| LMArena WebDev | 1244 | Not measured | Only Qwen3.5-Flash measured |
| LiveCodeBench (Vals AI) | 83.3% | Not measured | Only Qwen3.5-Flash measured |
| SWE-bench Verified (Vals AI) | 64.4% | Not measured | Only Qwen3.5-Flash measured |
| ALE-Bench | 265.9 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: coding | 1412 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: software and IT | 1416 | Not measured | Only Qwen3.5-Flash measured |
| LMArena WebDev: React | 1229 | Not measured | Only Qwen3.5-Flash measured |
| LMArena WebDev: HTML | 1291 | Not measured | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen3.5-Flash | Relace Search | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 143.5 | Not measured | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen3.5-Flash | Relace Search | Leader |
|---|---|---|---|
| GPQA Diamond | 82.8% | Not measured | Only Qwen3.5-Flash measured |
| MMMU Pro (Vals AI) | 81.9% | Not measured | Only Qwen3.5-Flash measured |
| GPQA Diamond (Epoch AI run) | 82.3% | Not measured | Only Qwen3.5-Flash measured |
| Chess puzzles | 14.0% | Not measured | Only Qwen3.5-Flash measured |
| Mystery game puzzles | 20.0% | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts | 1403 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: expert | 1407 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts in English | 1409 | Not measured | Only Qwen3.5-Flash 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
| Benchmark | Qwen3.5-Flash | Relace Search | Leader |
|---|---|---|---|
| AIME | 92.5% | Not measured | Only Qwen3.5-Flash measured |
| OTIS Mock AIME | 84.4% | Not measured | Only Qwen3.5-Flash measured |
| FrontierMath, tiers 1 to 3 | 18.2% | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: math | 1407 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: mathematical work | 1413 | Not measured | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | Qwen3.5-Flash | Relace Search | Leader |
|---|---|---|---|
| MMLU Pro | 84.1% | Not measured | Only Qwen3.5-Flash measured |
| LegalBench (Vals AI) | 84.3% | Not measured | Only Qwen3.5-Flash measured |
| CaseLaw (Vals AI) | 56.0% | Not measured | Only Qwen3.5-Flash measured |
| CorpFin (Vals AI) | 63.6% | Not measured | Only Qwen3.5-Flash measured |
| TaxEval (Vals AI) | 72.2% | Not measured | Only Qwen3.5-Flash measured |
| MortgageTax (Vals AI) | 67.4% | Not measured | Only Qwen3.5-Flash measured |
| MedCode (Vals AI) | 33.0% | Not measured | Only Qwen3.5-Flash measured |
| SimpleQA Verified | 20.3% | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: science | 1415 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: medicine and healthcare | 1407 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: legal and government | 1398 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: business and finance | 1394 | Not measured | Only Qwen3.5-Flash measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards measured
| Benchmark | Qwen3.5-Flash | Relace Search | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 42.5% | Not measured | Only Qwen3.5-Flash measured |
| MedScribe (Vals AI) | 70.6% | Not measured | Only Qwen3.5-Flash measured |
| DTBench | 82.9% | Not measured | Only Qwen3.5-Flash measured |
| LMCA | 29.1% | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text | 1397 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: instruction following | 1374 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: creative writing | 1343 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: English | 1404 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: non-English | 1385 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: Chinese | 1445 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: German | 1390 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: Japanese | 1369 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: Korean | 1344 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: French | 1413 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: Spanish | 1400 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: Russian | 1380 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: Polish | 1376 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: multi-turn | 1393 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: longer queries | 1392 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: writing and language | 1369 | Not measured | Only Qwen3.5-Flash measured |
| LMArena Text: entertainment and media | 1347 | Not measured | Only Qwen3.5-Flash 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
Qwen3.5-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-Flash 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 | Qwen3.5-Flash | Relace Search |
|---|---|---|
| Maker | Qwen | Relace |
| Weights | No public weights listed | No public weights listed |
| Released | February 25, 2026 | December 8, 2025 |
| Context window | 1M | 256K |
| Input $/Mtok | $0.065 | $1.00 |
| Output $/Mtok | $0.26 | $3.00 |
| Coding index | 41.1 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | $0.40 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.5-Flash better than Relace Search for coding?
Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Relace Search has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Qwen3.5-Flash or Relace Search?
Qwen3.5-Flash costs $0.065 per million input tokens and $0.26 per million output tokens; Relace Search costs $1.00 and $3.00. Cost per solved task is known for Qwen3.5-Flash only.
Which has the bigger context window, Qwen3.5-Flash or Relace Search?
Qwen3.5-Flash, with 1M tokens against 256K.
Has any benchmark tested both Qwen3.5-Flash and Relace Search?
No benchmark has tested both yet. Qwen3.5-Flash has results on LMArena WebDev, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); Relace Search has none yet. Compare them on price and context instead. Data as of October 22, 2026.