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Llama 3.3 70B Instruct vs Reka Edge

Reka Edge costs 7.2x less per output token than Llama 3.3 70B Instruct ($0.10 vs $0.72 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Llama 3.3 70B InstructMeta Llama
Coding
No data
Overall
26.0
Output $/M
$0.72
Reka EdgeReka
Coding
No data
Overall
No data
Output $/M
$0.10
vs $0.72 vs $0.10 per 1M output tokens. Reka Edge is 7.2x cheaper.

Llama 3.3 70B Instruct or Reka Edge: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Llama 3.3 70B Instruct for a larger context window (131K against 16K tokens).

No benchmark has tested both yet. Llama 3.3 70B Instruct has results on AA Coding Index, LiveCodeBench (Artificial Analysis run) and Terminal-Bench Hard (Artificial Analysis run); Reka Edge 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.

At a glance

Coding index
Llama 3.3 70B Instruct not benchmarked, Reka Edge 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
Llama 3.3 70B Instruct $0.72 against Reka Edge $0.10 per million output tokens, 7.2x apart.
Context window
Llama 3.3 70B Instruct takes 131K tokens, Reka Edge 16K.

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 Index6 boards measured
Coding benchmarks for Llama 3.3 70B Instruct and Reka Edge
BenchmarkLlama 3.3 70B InstructReka EdgeLeader
AA Coding Index11.9Not measuredOnly Llama 3.3 70B Instruct measured
LiveCodeBench (Artificial Analysis run)28.8%Not measuredOnly Llama 3.3 70B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)3.0%Not measuredOnly Llama 3.3 70B Instruct measured
WeirdML14.4%Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: coding1268Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: software and IT1273Not measuredOnly Llama 3.3 70B Instruct measured
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for Llama 3.3 70B Instruct and Reka Edge
BenchmarkLlama 3.3 70B InstructReka EdgeLeader
AA Intelligence Index7.7Not measuredOnly Llama 3.3 70B Instruct measured
Epoch Capabilities Index127.3Not measuredOnly Llama 3.3 70B Instruct measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
Agentic work benchmarks for Llama 3.3 70B Instruct and Reka Edge
BenchmarkLlama 3.3 70B InstructReka EdgeLeader
τ²-Bench Telecom26.6%Not measuredOnly Llama 3.3 70B Instruct measured
BALROG23.0%Not measuredOnly Llama 3.3 70B Instruct measured
Berkeley Function Calling Leaderboard (BFCL)31.9%Not measuredOnly Llama 3.3 70B Instruct measured
Neither model has a result on the other 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
Reasoning benchmarks for Llama 3.3 70B Instruct and Reka Edge
BenchmarkLlama 3.3 70B InstructReka EdgeLeader
GPQA Diamond (Artificial Analysis run)49.8%Not measuredOnly Llama 3.3 70B Instruct measured
Humanity's Last Exam (Artificial Analysis run)3.6%Not measuredOnly Llama 3.3 70B Instruct measured
GPQA Diamond (Epoch AI run)47.4%Not measuredOnly Llama 3.3 70B Instruct measured
SimpleBench19.9%Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: hard prompts1257Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: expert1225Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: hard prompts in English1277Not measuredOnly Llama 3.3 70B Instruct measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Math benchmarks for Llama 3.3 70B Instruct and Reka Edge
BenchmarkLlama 3.3 70B InstructReka EdgeLeader
AA Math Index7.7Not measuredOnly Llama 3.3 70B Instruct measured
AIME 2025 (Artificial Analysis run)7.7%Not measuredOnly Llama 3.3 70B Instruct measured
OTIS Mock AIME5.1%Not measuredOnly Llama 3.3 70B Instruct measured
MATH level 541.6%Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: math1267Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: mathematical work1267Not measuredOnly Llama 3.3 70B Instruct measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
Knowledge benchmarks for Llama 3.3 70B Instruct and Reka Edge
BenchmarkLlama 3.3 70B InstructReka EdgeLeader
MMLU Pro (Artificial Analysis run)71.3%Not measuredOnly Llama 3.3 70B Instruct measured
MMLU86.3%Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: science1284Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: medicine and healthcare1275Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: legal and government1284Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: business and finance1243Not measuredOnly Llama 3.3 70B Instruct measured
Neither model has a result on the other 14 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards measured
General benchmarks for Llama 3.3 70B Instruct and Reka Edge
BenchmarkLlama 3.3 70B InstructReka EdgeLeader
IFBench47.1%Not measuredOnly Llama 3.3 70B Instruct measured
Long context reasoning (AA-LCR)15.7%Not measuredOnly Llama 3.3 70B Instruct measured
DTBench59.5%Not measuredOnly Llama 3.3 70B Instruct measured
LMCA17.5%Not measuredOnly Llama 3.3 70B Instruct measured
Fiction.LiveBench33.3%Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text1274Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: instruction following1242Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: creative writing1250Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: English1303Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: non-English1236Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: Chinese1217Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: German1251Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: Japanese1150Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: Korean1142Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: French1282Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: Spanish1269Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: Russian1252Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: Polish1259Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: multi-turn1280Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: longer queries1255Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: writing and language1255Not measuredOnly Llama 3.3 70B Instruct measured
LMArena Text: entertainment and media1241Not measuredOnly Llama 3.3 70B Instruct measured
Neither model has a result on the other 26 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

Llama 3.3 70B Instruct$0.0008Fits in one request
Reka Edge$0.0001Fits in one request

Reka Edge costs less

Repository review

50K input + 3K output tokens

Llama 3.3 70B Instruct$0.025Fits in one request
Reka Edge$0.0053Exceeds the context window

Reka Edge costs less

Agent loop

200K input + 10K output tokens

Llama 3.3 70B Instruct$0.097Exceeds the context window
Reka Edge$0.021Exceeds the context window

Reka Edge 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 Llama 3.3 70B Instruct and Reka Edge
SpecificationMeta Llama 3.3 70B InstructReka Edge
MakerMeta LlamaReka
WeightsOpen weightsOpen weights
ReleasedDecember 6, 2024March 20, 2026
Context window131K16K
Input $/Mtok$0.45$0.10
Output $/Mtok$0.72$0.10
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Llama 3.3 70B Instruct better than Reka Edge for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.3 70B Instruct for a larger context window (131K against 16K tokens).

Which is cheaper, Llama 3.3 70B Instruct or Reka Edge?

Llama 3.3 70B Instruct costs $0.45 per million input tokens and $0.72 per million output tokens; Reka Edge costs $0.10 and $0.10. Cost per solved task is known for neither of them.

Which has the bigger context window, Llama 3.3 70B Instruct or Reka Edge?

Llama 3.3 70B Instruct, with 131K tokens against 16K.

Has any benchmark tested both Llama 3.3 70B Instruct and Reka Edge?

No benchmark has tested both yet. Llama 3.3 70B Instruct has results on AA Coding Index, LiveCodeBench (Artificial Analysis run) and Terminal-Bench Hard (Artificial Analysis run); Reka Edge has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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