Mixtral 8x22B Instruct vs Beam 1.0 501B A23B
Beam 1.0 501B A23B costs 5.5x less per output token than Mixtral 8x22B Instruct ($1.10 vs $6.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $6.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.10
Mixtral 8x22B Instruct or Beam 1.0 501B A23B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Mixtral 8x22B Instruct has results on LiveCodeBench (Artificial Analysis run), SciCode and AA Intelligence Index; Beam 1.0 501B A23B on LMArena WebDev, LMArena Text: coding and LMArena Text: software and IT. 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Mixtral 8x22B Instruct has a AA Intelligence Index result, 5.7.
Directional only
Web design
Design Arena: websites
No call
Only Beam 1.0 501B A23B has a Design Arena: websites result, 1253.
Directional only
Long documents
Listed context window
Beam 1.0 501B A23B
Beam 1.0 501B A23B takes 1.05M tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
Mixtral 8x22B Instruct $0.0050, Beam 1.0 501B A23B $0.0009 per turn.
List prices
At a glance
- Coding index
- Mixtral 8x22B Instruct not benchmarked, Beam 1.0 501B A23B 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
- Mixtral 8x22B Instruct $6.00 against Beam 1.0 501B A23B $1.10 per million output tokens, 5.5x apart.
- Context window
- Mixtral 8x22B Instruct takes 66K tokens, Beam 1.0 501B A23B 1.05M.
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 Index7 boards measured
| Benchmark | Mixtral 8x22B Instruct | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1437 | Only Beam 1.0 501B A23B measured |
| LiveCodeBench (Artificial Analysis run) | 14.8% | Not measured | Only Mixtral 8x22B Instruct measured |
| LMArena Text: coding | Not measured | 1473 | Only Beam 1.0 501B A23B measured |
| LMArena Text: software and IT | Not measured | 1461 | Only Beam 1.0 501B A23B measured |
| LMArena WebDev: React | Not measured | 1443 | Only Beam 1.0 501B A23B measured |
| LMArena WebDev: HTML | Not measured | 1436 | Only Beam 1.0 501B A23B measured |
| SciCode | 0.0% | Not measured | Only Mixtral 8x22B Instruct measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Mixtral 8x22B Instruct | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.7 | Not measured | Only Mixtral 8x22B Instruct measured |
| Epoch Capabilities Index | 122.0 | Not measured | Only Mixtral 8x22B Instruct measured |
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Mixtral 8x22B Instruct | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 33.2% | Not measured | Only Mixtral 8x22B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.0% | Not measured | Only Mixtral 8x22B Instruct measured |
| LMArena Text: hard prompts | Not measured | 1442 | Only Beam 1.0 501B A23B measured |
| LMArena Text: expert | Not measured | 1447 | Only Beam 1.0 501B A23B measured |
| LMArena Text: hard prompts in English | Not measured | 1451 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Mixtral 8x22B Instruct | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1459 | Only Beam 1.0 501B A23B measured |
| LMArena Text: mathematical work | Not measured | 1475 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Mixtral 8x22B Instruct | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 53.7% | Not measured | Only Mixtral 8x22B Instruct measured |
| LMArena Text: science | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| LMArena Text: medicine and healthcare | Not measured | 1376 | Only Beam 1.0 501B A23B measured |
| LMArena Text: legal and government | Not measured | 1433 | Only Beam 1.0 501B A23B measured |
| LMArena Text: business and finance | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 13 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Mixtral 8x22B Instruct | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1253 | Only Beam 1.0 501B A23B measured |
| Design Arena: game dev | Not measured | 1233 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 7 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index13 boards measured
| Benchmark | Mixtral 8x22B Instruct | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| DTBench | 55.1% | Not measured | Only Mixtral 8x22B Instruct measured |
| LMArena Text | Not measured | 1425 | Only Beam 1.0 501B A23B measured |
| LMArena Text: instruction following | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| LMArena Text: creative writing | Not measured | 1390 | Only Beam 1.0 501B A23B measured |
| LMArena Text: English | Not measured | 1436 | Only Beam 1.0 501B A23B measured |
| LMArena Text: non-English | Not measured | 1413 | Only Beam 1.0 501B A23B measured |
| LMArena Text: Chinese | Not measured | 1424 | Only Beam 1.0 501B A23B measured |
| LMArena Text: French | Not measured | 1461 | Only Beam 1.0 501B A23B measured |
| LMArena Text: Russian | Not measured | 1412 | Only Beam 1.0 501B A23B measured |
| LMArena Text: multi-turn | Not measured | 1414 | Only Beam 1.0 501B A23B measured |
| LMArena Text: longer queries | Not measured | 1429 | Only Beam 1.0 501B A23B measured |
| LMArena Text: writing and language | Not measured | 1400 | Only Beam 1.0 501B A23B measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 33 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 Mixtral 8x22B Instruct | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | Mistral AI | Reflection |
| Weights | Open weights | Open weights |
| Released | April 17, 2024 | October 16, 2026 |
| Context window | 66K | 1.05M |
| Input $/Mtok | $2.00 | $0.35 |
| Output $/Mtok | $6.00 | $1.10 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mixtral 8x22B Instruct better than Beam 1.0 501B A23B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Mixtral 8x22B Instruct or Beam 1.0 501B A23B?
Mixtral 8x22B Instruct costs $2.00 per million input tokens and $6.00 per million output tokens; Beam 1.0 501B A23B costs $0.35 and $1.10. Cost per solved task is known for neither of them.
Which has the bigger context window, Mixtral 8x22B Instruct or Beam 1.0 501B A23B?
Beam 1.0 501B A23B, with 1.05M tokens against 66K.
Has any benchmark tested both Mixtral 8x22B Instruct and Beam 1.0 501B A23B?
No benchmark has tested both yet. Mixtral 8x22B Instruct has results on LiveCodeBench (Artificial Analysis run), SciCode and AA Intelligence Index; Beam 1.0 501B A23B on LMArena WebDev, LMArena Text: coding and LMArena Text: software and IT. Compare them on price and context instead. Data as of October 21, 2026.