StarCoder2 alternatives

7 tools we tested head to head against StarCoder2, ranked — and what each one actually does differently.

last reviewed 29 jul 2026 · from our best 8 coding llms ·list curated by Onur Ozcanx in

first — what you'd be leaving

StarCoder2 ranks #7 of 8 in our coding llms testing. 600 languages at two gigabytes, under a licence whose conditions you have to pass on to your own users..

66/100

still the best small multi-language coder and two and a half years old — with commercial permission that comes with strings attached to your own terms of service.

why people look for an alternative

−openrail-m restrictions must be passed to your end users
−disclosure obligation on public-facing generated content
−no update since february 2024
−16k context with 4k sliding-window attention

stay with StarCoder2 if 600+ programming languages via the stack v2 is the thing you care about most — nothing below beats it on that.

the short version

best alternativeQwen3-Coderrepository-scale agentic work where the context window and the licence both need to be unrestricted.90/100

Qwen3-Coder

#1 in coding llms · apache 2.0 confirmed in the licence text, a million tokens of context, and now a version small enough to actually run.

90/100

verdictthe cleanest licence and the longest context in the category, with a february variant that finally makes it deployable outside a datacentre.

Qwen3-Coder vs StarCoder2

	StarCoder2	Qwen3-Coder
price	free (openrail-m)	free (apache 2.0)
free tier	yes	yes
licence	bigcode openrail-m v1	apache 2.0
params	3b, 7b, 15b	480b/35b active; next 80b/3b
context	16k, 4k sliding window	262k, 1m via yarn
commercial use	permitted with use restrictions	unrestricted
runs on	~2-9gb at 4-bit	~240gb, or ~40gb for next

switch forrepository-scale agentic work where the context window and the licence both need to be unrestricted.

pros

+plain apache 2.0, verified in the licence file
+262k native context extending to 1m via yarn
+qwen3-coder-next brings it to ~40gb for local use
+38.7 on swe-bench pro from the model's own repo

cons

−flagship needs ~240gb at 4-bit — server only
−swe-bench verified figures conflict across sources
−fill-in-the-middle support unconfirmed for this generation
−two very different models under one name

visit Qwen3-Coder →full Qwen3-Coder review →

DeepSeek Coder

#2 in coding llms · the brand is now an api alias — and the models behind it went from a restrictive weights licence to plain mit.

88/100

verdictthe strongest swe-bench numbers here under a licence that got more permissive rather than less — with no small variant left for anyone who wanted the original.

DeepSeek Coder vs StarCoder2

	StarCoder2	DeepSeek Coder
price	free (openrail-m)	free (mit)
free tier	yes	yes
licence	bigcode openrail-m v1	mit
params	3b, 7b, 15b	284b/13b active (flash)
context	16k, 4k sliding window	not confirmed per variant
commercial use	permitted with use restrictions	unrestricted
runs on	~2-9gb at 4-bit	~140gb at 4-bit

switch forfrontier-tier coding where the score matters more than running it yourself.

pros

+plain mit on both code and weights, a genuine loosening
+80.6% swe-bench verified on v4-pro
+frontier-tier coding without a licence negotiation
+one-million-token-scale context in the v4 family

cons

−no standalone coder models remain — it's an api alias
−smallest option needs ~140gb at 4-bit
−nothing runs locally, unlike the original 1.3b-33b line
−fill-in-the-middle support unconfirmed for v4

visit DeepSeek Coder →full DeepSeek Coder review →

Seed-Coder-8B

#3 in coding llms · plain mit, native fill-in-the-middle, and it fits in five gigabytes — the practical local pick.

84/100

verdictthe best thing here that actually runs on a laptop, with the cleanest licence and the fill-in-the-middle training the frontier models skipped.

Seed-Coder-8B vs StarCoder2

	StarCoder2	Seed-Coder-8B
price	free (openrail-m)	free (mit)
free tier	yes	yes
licence	bigcode openrail-m v1	mit
params	3b, 7b, 15b	8b
context	16k, 4k sliding window	32k tokens
commercial use	permitted with use restrictions	unrestricted
runs on	~2-9gb at 4-bit	~5gb at 4-bit

switch foreditor completion on your own machine, where latency beats leaderboard position.

pros

+plain mit with no conditions
+native fill-in-the-middle and spm training
+~5gb at 4-bit — genuinely local
+humaneval 84.8 and mbpp 85.2 self-reported

cons

−8b is the only size — no larger variant
−no update since june 2025
−32k context, shortest among the current models here
−cannot match frontier agentic coders on large repos

visit Seed-Coder-8B →full Seed-Coder-8B review →

Granite (IBM)

#4 in coding llms · apache 2.0, native fim, half a million tokens of context — and the dedicated code line is officially deprecated.

80/100

verdictthe cleanest licensing story in this ranking and native fim at 5gb — on a product line ibm has folded into its general models.

Granite (IBM) vs StarCoder2

	StarCoder2	Granite (IBM)
price	free (openrail-m)	free (apache 2.0)
free tier	yes	yes
licence	bigcode openrail-m v1	apache 2.0
params	3b, 7b, 15b	3b, 8b, 30b dense
context	16k, 4k sliding window	512k in 4.1
commercial use	permitted with use restrictions	unrestricted
runs on	~2-9gb at 4-bit	~5gb at 4-bit (8b)

switch forenterprises wanting unambiguous licensing and very long context at sizes that run locally.

pros

+apache 2.0 with licence and documentation in agreement
+cryptographically signed weights
+native fill-in-the-middle support
+512k context in granite 4.1 at ~5gb for the 8b

cons

−dedicated granite code line explicitly deprecated
−coding is now a general-model capability, not a specialism
−trails dedicated coders on pure code benchmarks
−legacy code models capped at 4k context

visit Granite (IBM) →full Granite (IBM) review →

Devstral

#5 in coding llms · the small one is apache 2.0 and the big one stops working for you the month you pass $20m in revenue.

77/100

verdicttwo models, two licences, and mistral says so plainly — which after codestral from the same company is a meaningful improvement in candour.

Devstral vs StarCoder2

	StarCoder2	Devstral
price	free (openrail-m)	free below the threshold
free tier	yes	yes
licence	bigcode openrail-m v1	modified mit (123b), apache (24b)
params	3b, 7b, 15b	123b and 24b
context	16k, 4k sliding window	128k on small
commercial use	permitted with use restrictions	capped at $20m/month on 123b
runs on	~2-9gb at 4-bit	~14gb (24b), ~70gb (123b)

switch foragentic coding scaffolds, at 24b for anyone, at 123b for companies under the revenue line.

pros

+devstral small 24b is plain apache 2.0
+mistral states the licence split explicitly
+purpose-built for agentic coding scaffolds
+24b runs in about 14gb at 4-bit

cons

−123b rights revoked above $20m monthly revenue
−hard cutoff rather than a graduated licence fee
−fill-in-the-middle support unconfirmed
−devstral 2's context length not confirmed

visit Devstral →full Devstral review →

GLM-4.6

#6 in coding llms · near-frontier coding under what its badge says is mit — and the licence file itself returns 404.

72/100

verdictreportedly close to claude sonnet 4 on real-world coding, with the one thing this ranking insists on — a readable licence — missing.

GLM-4.6 vs StarCoder2

	StarCoder2	GLM-4.6
price	free (openrail-m)	free (mit, unverified)
free tier	yes	yes
licence	bigcode openrail-m v1	mit per tag, file unreadable
params	3b, 7b, 15b	~355b
context	16k, 4k sliding window	200k tokens
commercial use	permitted with use restrictions	unrestricted, unverified
runs on	~2-9gb at 4-bit	~180gb at 4-bit

switch forhosted agentic coding through claude code or cline-style tooling, where you won't be self-hosting anyway.

pros

+reported near-parity with claude sonnet 4 on cc-bench
+200k context, up from 128k in glm-4.5
+built for claude code and cline-style integration
+mit per the hugging face licence tag

cons

−raw licence file returned 404 — text unverified
−~180gb at 4-bit, datacentre only
−superseded by glm-5.1 and 5.2 as general flagships
−no primary benchmark figure retrievable from zhipu

visit GLM-4.6 →full GLM-4.6 review →

Codestral

#8 in coding llms · downloadable, and forbidden in production — the licence is a flat non-commercial bar, not a threshold.

58/100

verdictthe most restrictive licence in this ranking by a distance, on a model whose current iteration may not have open weights at all.

Codestral vs StarCoder2

	StarCoder2	Codestral
price	free (openrail-m)	research use only
free tier	yes	yes
licence	bigcode openrail-m v1	mistral non-production licence
params	3b, 7b, 15b	22b (open checkpoint)
context	16k, 4k sliding window	128k tokens
commercial use	permitted with use restrictions	prohibited without a paid licence
runs on	~2-9gb at 4-bit	~13gb at 4-bit

switch forresearch, evaluation and prototypes that will never ship.

pros

+long-established fill-in-the-middle tuned for editors
+128k context on the documented model card
+22b runs in about 13gb for research use
+available as a supported paid api

cons

−non-production licence bars commercial use entirely
−commercial terms require a private negotiation
−current 25.08 iteration appears to be api-only
−launch framing understates the prohibition

visit Codestral →full Codestral review →

how these were compared

every tool on this page went through the same test as StarCoder2 — same tasks, same order, scored the same way. the comparison tables are the figures from that testing, not vendor spec sheets.

the coding llms test in full →

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