Mistral Medium 3.5 vs Beam 1.0 501B A23B
Updated October 21, 2026. 28 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Beam 1.0 501B A23B for coding: it scores 33.8 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5.
Pick Mistral Medium 3.5 when what matters is LMArena Text: medicine and healthcare or LMArena Text: legal and government, where it leads.
- Shared results
- 28
- Mistral Medium 3.5 only
- 52
- Beam 1.0 501B A23B only
- 0
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Beam 1.0 501B A23B
Beam 1.0 501B A23B scores 33.8 against 9.2.
One benchmark behind each score
Intelligence
AA Intelligence Index
No call
Only Mistral Medium 3.5 has a AA Intelligence Index result, 14.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.5 has a AA Agentic Index result, 7.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Medium 3.5 has a GPQA Diamond result, 34.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.5 has a MMLU Pro result, 75.3%.
Directional only
Web design
Design Arena: websites
Beam 1.0 501B A23B
Beam 1.0 501B A23B leads, 1253 against 1142.
Same board, both measured
Long documents
Listed context window
Beam 1.0 501B A23B
Beam 1.0 501B A23B takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
Mistral Medium 3.5 $0.0053, Beam 1.0 501B A23B $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Medium 3.5 has the number, $6.02.
Directional only
At a glance
- Coding index
- Mistral Medium 3.5 9.2 from 1 benchmark, Beam 1.0 501B A23B 33.8 from 1 benchmark.
- Widest category
- Coding, 16.0 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Mistral Medium 3.5 1254 against Beam 1.0 501B A23B 1443, 31.4 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.5 $7.50 against Beam 1.0 501B A23B $1.00 per million output tokens, 7.5x apart.
- Context window
- Mistral Medium 3.5 takes 262K tokens, Beam 1.0 501B A23B 1.05M.
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.
| Category | Mistral Medium 3.5 | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 2 | 2 | ||
| Web design | 0 | 2 | ||
| General | 2 | 10 | ||
| All shared boards | 4 | 24 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index05
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena WebDev | 1264 | 1437 | Beam 1.0 501B A23B |
| AA Coding Index | 46.9 | Not measured | Only Mistral Medium 3.5 measured |
| SWE-bench Verified (Vals AI) | 66.4% | Not measured | Only Mistral Medium 3.5 measured |
| Vibe Code Bench (Vals AI) | 2.9% | Not measured | Only Mistral Medium 3.5 measured |
| Code migration (Vals AI) | 5.1% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 39.0% | Not measured | Only Mistral Medium 3.5 measured |
| SciCode | 40.2% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only Mistral Medium 3.5 measured |
| ALE-Bench | 764.0 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: coding | 1460 | 1473 | Beam 1.0 501B A23B |
| LMArena Text: software and IT | 1458 | 1461 | Beam 1.0 501B A23B |
| LMArena WebDev: React | 1254 | 1443 | Beam 1.0 501B A23B |
| LMArena WebDev: HTML | 1308 | 1436 | Beam 1.0 501B A23B |
| Neither model has a result on the other 25 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.2 | Not measured | Only Mistral Medium 3.5 measured |
| Epoch Capabilities Index | 141.4 | Not measured | Only Mistral Medium 3.5 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Agentic Index | 7.0 | Not measured | Only Mistral Medium 3.5 measured |
| Finance Agent (Vals AI) | 32.1% | Not measured | Only Mistral Medium 3.5 measured |
| Tax Agent Bench (Vals AI) | 4.5% | Not measured | Only Mistral Medium 3.5 measured |
| Legal Research Bench (Vals AI) | 9.1% | Not measured | Only Mistral Medium 3.5 measured |
| Excel Modeling Benchmark (Vals AI) | 11.2% | Not measured | Only Mistral Medium 3.5 measured |
| τ²-Bench Telecom | 94.2% | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| GPQA Diamond | 34.9% | Not measured | Only Mistral Medium 3.5 measured |
| GPQA Diamond (Artificial Analysis run) | 74.8% | Not measured | Only Mistral Medium 3.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 13.8% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: hard prompts | 1436 | 1442 | Beam 1.0 501B A23B |
| LMArena Text: expert | 1432 | 1447 | Beam 1.0 501B A23B |
| LMArena Text: hard prompts in English | 1445 | 1451 | Beam 1.0 501B A23B |
| LMArena Vision: diagrams | 1254 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: homework | 1230 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: math | 1431 | 1459 | Beam 1.0 501B A23B |
| LMArena Text: mathematical work | 1440 | 1475 | Beam 1.0 501B A23B |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | Not measured | Only Mistral Medium 3.5 measured |
| CaseLaw (Vals AI) | 44.2% | Not measured | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | 58.8% | Not measured | Only Mistral Medium 3.5 measured |
| TaxEval (Vals AI) | 68.0% | Not measured | Only Mistral Medium 3.5 measured |
| MortgageTax (Vals AI) | 28.9% | Not measured | Only Mistral Medium 3.5 measured |
| MedCode (Vals AI) | 33.8% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: science | 1428 | 1430 | Beam 1.0 501B A23B |
| LMArena Text: medicine and healthcare | 1409 | 1376 | Mistral Medium 3.5 |
| LMArena Text: legal and government | 1437 | 1433 | Mistral Medium 3.5 |
| LMArena Text: business and finance | 1426 | 1430 | Beam 1.0 501B A23B |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | 1142 | 1253 | Beam 1.0 501B A23B |
| Design Arena: UI components | 1079 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: game dev | 1079 | 1222 | Beam 1.0 501B A23B |
| Design Arena: data viz | 1120 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | 1061 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | 1122 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: SVG | 949 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | 1062 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index210
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 37.6% | Not measured | Only Mistral Medium 3.5 measured |
| MedScribe (Vals AI) | 67.7% | Not measured | Only Mistral Medium 3.5 measured |
| Vals Multimodal Index | 34.8% | Not measured | Only Mistral Medium 3.5 measured |
| IFBench | 68.8% | Not measured | Only Mistral Medium 3.5 measured |
| Long context reasoning (AA-LCR) | 69.3% | Not measured | Only Mistral Medium 3.5 measured |
| DTBench | 75.5% | Not measured | Only Mistral Medium 3.5 measured |
| LMCA | 26.1% | Not measured | Only Mistral Medium 3.5 measured |
| Surface Evolver Bench | 26.9% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text | 1421 | 1425 | Beam 1.0 501B A23B |
| LMArena Text: instruction following | 1415 | 1430 | Beam 1.0 501B A23B |
| LMArena Text: creative writing | 1374 | 1390 | Beam 1.0 501B A23B |
| LMArena Vision | 1222 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: English | 1433 | 1436 | Beam 1.0 501B A23B |
| LMArena Text: non-English | 1404 | 1413 | Beam 1.0 501B A23B |
| LMArena Text: Chinese | 1444 | 1424 | Mistral Medium 3.5 |
| LMArena Text: German | 1453 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Korean | 1384 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: French | 1448 | 1461 | Beam 1.0 501B A23B |
| LMArena Text: Spanish | 1411 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Russian | 1395 | 1412 | Beam 1.0 501B A23B |
| LMArena Text: Polish | 1430 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: multi-turn | 1423 | 1414 | Mistral Medium 3.5 |
| LMArena Text: longer queries | 1415 | 1429 | Beam 1.0 501B A23B |
| LMArena Text: writing and language | 1384 | 1400 | Beam 1.0 501B A23B |
| LMArena Text: entertainment and media | 1382 | 1399 | Beam 1.0 501B A23B |
| LMArena Vision: English | 1240 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: Chinese | 1244 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: reading text | 1233 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: humor | 1216 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: creative writing | 1198 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Medium 3.5 | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| 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
Beam 1.0 501B A23B costs less
Repository review
50K input + 3K output tokens
Beam 1.0 501B A23B costs less
Agent loop
200K input + 10K output tokens
Beam 1.0 501B A23B 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 | Mistral Medium 3.5 | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | Mistral AI | Reflection |
| Weights | No public weights listed | Open weights |
| Released | April 30, 2026 | October 16, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $1.50 | $0.30 |
| Output $/Mtok | $7.50 | $1.00 |
| Coding index | 9.2 | 33.8 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $6.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than Beam 1.0 501B A23B for coding?
Pick Beam 1.0 501B A23B for coding: it scores 33.8 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5. Pick Mistral Medium 3.5 when what matters is LMArena Text: medicine and healthcare or LMArena Text: legal and government, where it leads.
Which is cheaper, Mistral Medium 3.5 or Beam 1.0 501B A23B?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; Beam 1.0 501B A23B costs $0.30 and $1.00. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, Mistral Medium 3.5 or Beam 1.0 501B A23B?
Beam 1.0 501B A23B, with 1.05M tokens against 262K.
How many benchmarks is the Mistral Medium 3.5 vs Beam 1.0 501B A23B comparison based on?
28 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3.5's coding index rests on 1 independent benchmark and Beam 1.0 501B A23B's on 1. Where only one model has a result, the page says so instead of naming a winner.